GSS Analysis
For this lab on logistic regression, you will work through each of the chunks and respond to the questions. You should knit the notebook to html (not Word). Please submit your knitted html and Rmd to Sakai by Monday at noon.
We are using dta from the General Social Survey (GSS) which is a survey that occurs every few years and provides researchers and policymakers a better understanding of Americans views on a variety of policy issues. Please read more about the GSS here: https://gss.norc.org/About-The-GSS.
The central purpose of our modeling is to determine if there is a relationship between time spent in nature, access to nature and beliefs about spending on the environment.
Response Variable
natenvir is a variable that measures the response to the question:
I would like to talk with you about some things people think about today. We are faced with many problems in this country, none of which can be solved easily or inexpensively. I’m going to name some of these problems, and for each one I’d like you to tell me whether you think we’re spending too much money on it, too little money, or about the right amount: Improving the environment."
Explanatory Variables of Interest
nattime is a variable that captures the response to the question:
Usually, I spend time in natural environments, such as public parks, gardens or trails, at least once a week.
nataccess is a variable that captures the response to the question:
I have easy access to natural environments, such as public parks, gardens or trails.
Before you get started, please install the package “readstata13”. This package allows us to read in data from Stata (.dta).I downloaded the GSS data in .dta form from the website: https://gss.norc.org/get-the-data/stata.
library(ggplot2)
library(readstata13)## Warning: package 'readstata13' was built under R version 4.0.3library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionThe following chunk reads in the GSS data from the year 2018 and makes a dataframe which I have named gss. You will receive some messages about duplicated factor levels. That’s okay–please ignore.
gss<-read.dta13("GSS2018.dta", generate.factors=T, nonint.factors=T)## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## coisco08:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## coother:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## denkid:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## hhtype:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## isco08:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## madenkid:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## maisco08:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## oth16:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## other:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## padenkid:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## paisco08:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## socbar:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## socfrend:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## socommun:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## socrel:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## spisco08:
## Duplicated factor levels detected - generating unique labels.## Warning in read.dta13("GSS2018.dta", generate.factors = T, nonint.factors = T):
## spother:
## Duplicated factor levels detected - generating unique labels.In the chunk below, look at the structure of the gss dataframe and answer the following questions. Please answer in the white space below each of the questions.
Question 1 How many observations are in the dataset? (2 points)
Question 2 How many variables are in the dataset? (3 points)
glimpse(gss)## Rows: 2,348
## Columns: 1,065
## $ abany <fct> no, yes, NA, NA, no, yes, yes, no, NA, NA, yes, NA, n...
## $ abdefect <fct> yes, yes, NA, NA, yes, yes, yes, yes, NA, NA, yes, NA...
## $ abfelegl <fct> NA, it depends, NA, should, NA, should, it depends, N...
## $ abhelp1 <fct> yes, no, yes, yes, no, yes, yes, yes, yes, yes, yes, ...
## $ abhelp2 <fct> yes, no, no, yes, no, yes, no, no, yes, no, yes, no, ...
## $ abhelp3 <fct> yes, no, yes, yes, no, yes, yes, yes, yes, no, yes, n...
## $ abhelp4 <fct> yes, no, yes, yes, yes, yes, yes, yes, yes, yes, yes,...
## $ abhlth <fct> yes, yes, NA, NA, yes, yes, yes, yes, NA, NA, yes, NA...
## $ abinspay <fct> people should be able, people should not be able, peo...
## $ abmedgov1 <fct> the government should decide, NA, a woman and her med...
## $ abmedgov2 <fct> NA, a woman and her medical professional should decid...
## $ abmelegl <fct> it depends, NA, it depends, NA, it depends, NA, NA, i...
## $ abmoral <fct> morally opposed, it depends, it depends, it depends, ...
## $ abnomore <fct> no, yes, NA, NA, no, yes, yes, no, NA, NA, yes, NA, n...
## $ abpoor <fct> no, no, NA, NA, no, yes, yes, no, NA, NA, yes, NA, no...
## $ abpoorw <fct> always wrong, NA, wrong only sometimes, NA, NA, not w...
## $ abrape <fct> yes, yes, NA, NA, no, yes, yes, yes, NA, NA, yes, NA,...
## $ absingle <fct> no, yes, NA, NA, no, yes, no, no, NA, NA, yes, NA, no...
## $ abstate1 <fct> neither easy nor hard, easy, very easy, easy, NA, eas...
## $ abstate2 <fct> make it harder, stay the same as now, make it harder,...
## $ acqntsex <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ actssoc <fct> very good, good, excellent, very good, excellent, goo...
## $ adminconsent <fct> r does not consent to possible data linkage, r does n...
## $ adults <fct> 5, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 3, 2, 2, 2,...
## $ advfront <fct> strongly agree, NA, disagree, NA, NA, strongly agree,...
## $ affrmact <fct> strongly oppose pref, NA, strongly oppose pref, oppos...
## $ afraidof <fct> never, never, NA, NA, a few times a month, never, a f...
## $ afterlif <fct> "yes, definitely", NA, "yes, definitely", NA, NA, "ye...
## $ age <fct> 43, 74, 42, 63, 71, 67, 59, 43, 62, 55, 59, 34, 61, 4...
## $ aged <fct> NA, a good idea, a good idea, a good idea, a bad idea...
## $ agekdbrn <fct> NA, 21, 35, 32, NA, 27, 18, NA, 17, 30, 30, 20, 20, 3...
## $ ancestrs <fct> "no, definitely not", NA, "no, probably not", NA, NA,...
## $ arthrtis <fct> no, NA, no, yes, NA, NA, no, no, yes, no, no, no, NA,...
## $ astrolgy <fct> no, NA, no, NA, NA, no, NA, NA, no, NA, yes, NA, yes,...
## $ astrosci <fct> not at all scientific, NA, not at all scientific, NA,...
## $ atheists <fct> somewhat negative, NA, neither positive nor negative,...
## $ attend <fct> 2-3x a month, once a year, once a year, nrly every we...
## $ attend12 <fct> every week, NA, several times a week, NA, NA, several...
## $ attendma <fct> every week, NA, several times a week, NA, NA, every w...
## $ attendpa <fct> about once or twice a yr, NA, every week, NA, NA, eve...
## $ away1 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ away11 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ away2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ away3 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, yes, NA, NA, NA, ...
## $ away4 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ away5 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ away6 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ away7 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ babies <fct> 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 2...
## $ backpain <fct> no, NA, no, yes, NA, NA, yes, no, yes, yes, no, no, N...
## $ ballot <fct> ballot a, ballot c, ballot b, ballot b, ballot c, bal...
## $ balneg <fct> slightly in favor, NA, NA, NA, NA, NA, NA, NA, NA, NA...
## $ balpos <fct> NA, NA, strongly in favor, NA, NA, strongly in favor,...
## $ befair <fct> NA, fair all of time, NA, fair mst of time, fair mst ...
## $ betrlang <fct> language 1, NA, NA, NA, NA, NA, language 1, NA, NA, N...
## $ bible <fct> word of god, word of god, inspired word, inspired wor...
## $ bigbang <fct> false, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, fa...
## $ bigbang1 <fct> NA, NA, true, NA, NA, NA, NA, NA, true, NA, NA, NA, N...
## $ bigbang2 <fct> NA, NA, NA, NA, NA, true, NA, NA, NA, NA, true, NA, N...
## $ bird <fct> NA, NA, NA, NA, does not have, NA, does not have, NA,...
## $ birdb4 <fct> NA, NA, NA, did not have, NA, NA, NA, NA, NA, NA, NA,...
## $ born <fct> yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes...
## $ boyorgrl <fct> true, NA, NA, NA, NA, true, NA, NA, NA, NA, true, NA,...
## $ breakdwn <fct> NA, very likely, NA, not very likely, not at all like...
## $ buddhsts <fct> neither positive nor negative, NA, somewhat positive,...
## $ buyesop <fct> i would be neither more nor less likely to buy from a...
## $ buyvalue <fct> NA, NA, 0, NA, NA, NA, NA, 35, NA, NA, NA, NA, NA, NA...
## $ cantrust <fct> NA, always trusted, NA, always trusted, usually trust...
## $ cappun <fct> favor, oppose, favor, oppose, oppose, favor, favor, f...
## $ cat <fct> NA, NA, NA, NA, does not have, NA, does not have, NA,...
## $ catb4 <fct> NA, NA, NA, did not have, NA, NA, NA, NA, NA, NA, NA,...
## $ charactr <fct> NA, somewhat likely, NA, not at all likely, not very ...
## $ chemgen <fct> extremely dangerous, NA, NA, NA, NA, very dangerous, ...
## $ childs <fct> 0, 3, 2, 2, 0, 2, 6, 0, 4, 2, 2, 3, 2, 2, 2, 4, 0, 2,...
## $ chldidel <fct> 2, NA, 2, 2, NA, 2, NA, NA, 2, 2, 3, 3, 2, NA, 2, 4, ...
## $ christns <fct> very positive, NA, somewhat positive, NA, NA, neither...
## $ churhpow <fct> far too litl pwr, NA, too much power, NA, NA, right a...
## $ class <fct> working class, working class, middle class, middle cl...
## $ clergvte <fct> disagree, NA, strongly agree, NA, NA, agree, NA, NA, ...
## $ closeto1 <fct> NA, 5, NA, 9, 3, NA, very close, 5, NA, 7, NA, very c...
## $ closeto2 <fct> NA, not close at all, NA, not close at all, not close...
## $ closeto3 <fct> NA, NA, NA, 7, very close, NA, not close at all, NA, ...
## $ closeto4 <fct> NA, NA, NA, 6, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
## $ closeto5 <fct> NA, NA, NA, not close at all, NA, NA, NA, NA, NA, NA,...
## $ cntctfam <fct> NA, several times a year, NA, several times a week, l...
## $ cntctfrd <fct> NA, once a week, NA, several times a week, several ti...
## $ cntctkid <fct> NA, daily, NA, daily, i do not have any adult childre...
## $ cntctpar <fct> NA, my parents are no longer alive, NA, my parents ar...
## $ cntctsib <fct> NA, several times a year, NA, daily, two to three ti...
## $ codeg <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, high school, ...
## $ coden <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ coeduc <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 12, NA, NA, N...
## $ coevwork <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ cofund <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, moderate, NA,...
## $ cohort <fct> 1975, 1944, 1976, 1955, 1947, 1951, 1959, 1975, 1956,...
## $ cohrs1 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 40, NA, NA, N...
## $ cohrs2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ coind10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, nursing care ...
## $ coisco08 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "cleaners and...
## $ cojew <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ colath <fct> allowed, not allowed, NA, NA, not allowed, allowed, a...
## $ colcom <fct> not fired, fired, NA, NA, not fired, not fired, fired...
## $ coldeg1 <fct> associate's, NA, bachelor's, NA, NA, bachelor's, NA, ...
## $ colhomo <fct> allowed, allowed, NA, NA, allowed, allowed, allowed, ...
## $ colmil <fct> allowed, not allowed, NA, NA, not allowed, allowed, n...
## $ colmslm <fct> "yes, allowed", "not allowed", NA, NA, "not allowed",...
## $ colrac <fct> allowed, not allowed, NA, NA, not allowed, allowed, a...
## $ colsci <fct> no, NA, yes, NA, NA, yes, NA, NA, no, NA, yes, NA, no...
## $ colscinm <fct> NA, NA, 20, NA, NA, 20, NA, NA, NA, NA, 3, NA, NA, NA...
## $ comfort <fct> agree, NA, agree, NA, NA, agree, NA, NA, strongly agr...
## $ company <fct> a company whose stock is owned by outside investors w...
## $ compperf <fct> no, NA, yes, NA, NA, NA, NA, NA, NA, NA, yes, NA, NA,...
## $ comprend <fct> good, good, good, good, good, good, good, good, good,...
## $ compuse <fct> yes, NA, yes, yes, NA, yes, NA, NA, no, yes, yes, yes...
## $ compwage <fct> 1 lower, NA, 5 higher, 1 lower, NA, NA, 3, 3, 1 lower...
## $ conarmy <fct> NA, a great deal, only some, a great deal, a great de...
## $ conbiz <fct> some confidence, NA, a great deal of confidence, NA, ...
## $ conbus <fct> NA, a great deal, only some, only some, a great deal,...
## $ conchurh <fct> some confidence, NA, very little confidence, NA, NA, ...
## $ conclerg <fct> NA, a great deal, hardly any, only some, a great deal...
## $ concong <fct> some confidence, NA, very little confidence, NA, NA, ...
## $ concourt <fct> very little confidence, NA, some confidence, NA, NA, ...
## $ condemnd <fct> not at all true, NA, somewhat true, not too true, NA,...
## $ condom <fct> NA, not used, used last time, used last time, not use...
## $ condrift <fct> true, NA, true, NA, NA, true, NA, NA, true, NA, true,...
## $ coneduc <fct> NA, a great deal, only some, hardly any, only some, N...
## $ conf2f <fct> NA, most of them, NA, most of them, some of them, NA,...
## $ confed <fct> NA, a great deal, only some, hardly any, only some, N...
## $ confinan <fct> NA, a great deal, hardly any, only some, a great deal...
## $ coninc <fct> NA, 22782.5, 112160, 158201.84123, 158201.84123, NA, ...
## $ conjudge <fct> NA, a great deal, a great deal, a great deal, a great...
## $ conlabor <fct> NA, a great deal, hardly any, only some, only some, N...
## $ conlegis <fct> NA, a great deal, hardly any, hardly any, hardly any,...
## $ conmedic <fct> NA, a great deal, a great deal, hardly any, a great d...
## $ conpress <fct> NA, a great deal, hardly any, hardly any, hardly any,...
## $ conrinc <fct> NA, NA, 70100, 84120, NA, NA, 13143.75, 26287.5, 1402...
## $ conschls <fct> some confidence, NA, some confidence, NA, NA, some co...
## $ consci <fct> NA, NA, a great deal, a great deal, a great deal, NA,...
## $ consent <fct> r consents to recording interview, r consents to reco...
## $ contv <fct> NA, a great deal, only some, only some, hardly any, N...
## $ conwkday <fct> NA, 5-9 people, NA, 20-49 people, 20-49 people, NA, 1...
## $ coocc10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "janitors and...
## $ coop <fct> "friendly,interested", "friendly,interested", "friend...
## $ coother <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ copres10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 24, NA, NA, N...
## $ copres105plus <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 15, NA, NA, N...
## $ corel <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, catholic, NA,...
## $ cosei10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 20.7, NA, NA,...
## $ cosei10educ <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 22.3, NA, NA,...
## $ cosei10inc <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 14.7, NA, NA,...
## $ courts <fct> not harsh enough, not harsh enough, not harsh enough,...
## $ cowrkhlp <fct> very true, NA, somewhat true, very true, NA, NA, some...
## $ cowrkint <fct> very true, NA, somewhat true, very true, NA, NA, some...
## $ cowrkslf <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, someone else,...
## $ cowrksta <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, working fullt...
## $ crack30 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ dangoth1 <fct> NA, not at all dangerous, NA, not at all dangerous, 5...
## $ dangoth2 <fct> NA, very dangerous, NA, 6, 5, NA, not at all dangerou...
## $ dangoth3 <fct> NA, NA, NA, not at all dangerous, not at all dangerou...
## $ dangoth4 <fct> NA, NA, NA, not at all dangerous, NA, NA, NA, NA, NA,...
## $ dangoth5 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ dangroth <fct> NA, yes, NA, yes, yes, NA, yes, yes, NA, yes, NA, yes...
## $ dangrslf <fct> NA, yes, NA, yes, yes, NA, yes, yes, NA, yes, NA, yes...
## $ dangslf1 <fct> NA, not at all dangerous, NA, not at all dangerous, N...
## $ dangslf2 <fct> NA, very dangerous, NA, 6, NA, NA, not at all dangero...
## $ dangslf3 <fct> NA, NA, NA, not at all dangerous, 5, NA, not at all d...
## $ dangslf4 <fct> NA, NA, NA, not at all dangerous, NA, NA, NA, NA, NA,...
## $ dangslf5 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ dateintv <fct> 907, 426, 910, 425, 718, 521, 418, 803, 505, 424, 508...
## $ decmoney <fct> NA, not very able, NA, somewhat able, very able, NA, ...
## $ dectreat <fct> NA, very able, NA, not very able, very able, NA, very...
## $ defpensn <fct> yes, NA, no, yes, NA, NA, no, yes, no, yes, no, no, N...
## $ degree <fct> junior college, high school, bachelor, bachelor, grad...
## $ demands <fct> NA, "yes, but seldom", NA, "no, never", "yes, sometim...
## $ denkid <fct> "baptist, dk which", NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ denom <fct> no denomination, NA, NA, united methodist, NA, NA, ba...
## $ denom16 <fct> baptist-dk which, NA, NA, NA, NA, NA, baptist-dk whic...
## $ depress <fct> no, NA, no, yes, NA, NA, no, no, yes, yes, no, no, NA...
## $ deptperf <fct> no, NA, no, NA, NA, NA, NA, NA, NA, NA, yes, NA, NA, ...
## $ diabetes <fct> no, NA, no, no, NA, NA, yes, no, no, no, no, no, NA, ...
## $ diagnosd <fct> NA, no, NA, yes, no, NA, no, no, NA, no, NA, no, NA, ...
## $ difrel <fct> disagree, NA, agree, NA, NA, disagree, NA, NA, disagr...
## $ dinefrds <fct> NA, never, NA, several times a year, two to three tim...
## $ dipged <fct> high school diploma, ged, high school diploma, high s...
## $ discaff <fct> somewhat likely, not very likely, NA, NA, not very li...
## $ discaffm <fct> somewhat unlikely, NA, somewhat unlikely, NA, NA, NA,...
## $ discaffw <fct> NA, NA, NA, somewhat unlikely, NA, somewhat likely, N...
## $ disrspct <fct> a few times a month, never, NA, NA, less than once a ...
## $ divlaw <fct> more difficult, NA, more difficult, easier, NA, more ...
## $ divorce <fct> NA, NA, no, no, NA, no, NA, NA, no, no, NA, NA, NA, n...
## $ dofirst <fct> NA, talk to family and friends about it, NA, go to a ...
## $ dog <fct> NA, NA, NA, NA, does not have, NA, has, NA, NA, does ...
## $ dogb4 <fct> NA, NA, NA, had, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ dwelling <fct> detached 1-fam house, detached 1-fam house, detached ...
## $ dwellpre <fct> "detached single family house", "detached single fami...
## $ dwelown <fct> pays rent, NA, own or is buying, own or is buying, NA...
## $ dwelown16 <fct> owned or was buying, NA, owned or was buying, owned o...
## $ earnrs <fct> 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 0, 1, 1, 2, 2, 1,...
## $ earthsun <fct> earth around sun, NA, earth around sun, NA, NA, earth...
## $ educ <fct> 14, 10, 16, 16, 18, 16, 13, 12, 8, 12, 19, 14, 13, 16...
## $ egomeans <fct> disagree, NA, neither agree nor disagree, NA, NA, agr...
## $ electron <fct> true, NA, false, NA, NA, NA, NA, NA, true, NA, true, ...
## $ emailhr <fct> 25, NA, 20, 7, NA, 2, NA, NA, 0, 2, 20, 1, 1, NA, 0, ...
## $ emailmin <fct> 0, NA, 0, 0, NA, 0, NA, NA, 0, 0, 0, 0, 0, NA, 0, 0, ...
## $ emoprobs <fct> rarely, rarely, sometimes, rarely, rarely, sometimes,...
## $ empinput <fct> no, NA, no, yes, NA, NA, no, no, no, no, yes, no, NA,...
## $ emptrain <fct> yes, NA, yes, no, NA, NA, no, no, no, no, no, yes, NA...
## $ endsmeet <fct> NA, neither easy nor difficult, NA, very easy, very e...
## $ eqwlth <fct> NA, no govt action, 3, 5, 6, NA, 5, govt reduce diff,...
## $ esop <fct> NA, NA, no, NA, NA, NA, NA, yes, NA, NA, NA, NA, NA, ...
## $ esopnot <fct> i would definitely take the job with the esop (employ...
## $ eth1 <fct> germany, italy, italy, france, scotland, england & wa...
## $ eth2 <fct> scotland, NA, other spanish, england & wales, ireland...
## $ eth3 <fct> NA, NA, NA, ireland, NA, germany, NA, puerto rico, NA...
## $ ethnic <fct> NA, italy, NA, ireland, scotland, ireland, other, ame...
## $ ethnum <fct> cannot choose 1, names 1, cannot choose 1, chooses 1 ...
## $ evcrack <fct> NA, no, no, no, no, NA, NA, no, no, no, NA, no, NA, n...
## $ evidu <fct> NA, no, no, no, no, NA, NA, no, no, no, NA, no, NA, n...
## $ evolved <fct> false, NA, true, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ evolved2 <fct> NA, NA, NA, NA, NA, true, NA, NA, true, NA, true, NA,...
## $ evpaidsx <fct> NA, no, no, no, no, NA, NA, no, no, no, NA, no, NA, n...
## $ evstray <fct> NA, no, no, yes, no, NA, NA, never married, no, no, N...
## $ evwork <fct> NA, yes, NA, NA, yes, yes, NA, NA, NA, NA, NA, NA, ye...
## $ expdesgn <fct> NA, NA, 500 get the drug 500 dont, NA, NA, 500 get th...
## $ exptext <fct> NA, NA, correct control group, NA, NA, correct vague ...
## $ extr2017 <fct> yes, NA, yes, NA, NA, NA, NA, NA, NA, NA, yes, NA, NA...
## $ extrapay <fct> yes, NA, yes, no, NA, NA, no, no, no, no, yes, no, NA...
## $ extraval <fct> NA, NA, 10000, NA, NA, NA, NA, NA, NA, NA, 10000, NA,...
## $ extrayr <fct> 2018, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ fair <fct> NA, take advantage, fair, fair, fair, NA, fair, take ...
## $ fairearn <fct> somewhat less than you deserve, NA, somewhat more tha...
## $ famdif16 <fct> NA, NA, "divorce,separated", NA, NA, NA, "divorce,sep...
## $ famgen <fct> "1 gen", "2 gens, children", "2 gens, children", "1 g...
## $ family16 <fct> mother & father, mother & father, father & stpmother,...
## $ fammhneg <fct> NA, somewhat, NA, not very much, not at all, NA, some...
## $ fampress <fct> NA, "no, never", NA, "no, never", "no, never", NA, "n...
## $ famvswk <fct> rarely, NA, sometimes, rarely, NA, NA, never, never, ...
## $ famwkoff <fct> somewhat hard, NA, not at all hard, not too hard, NA,...
## $ fatalism <fct> strongly disagree, NA, disagree, NA, NA, disagree, NA...
## $ fatigue <fct> mild, none, severe, mild, none, moderate, mild, none,...
## $ fear <fct> yes, no, NA, NA, no, no, yes, no, NA, NA, yes, NA, ye...
## $ fechld <fct> strongly agree, NA, strongly agree, agree, NA, strong...
## $ feelevel <fct> $75+, 25, $75+, 25, $75+, 25, 25, $75+, 25, 25, 25, $...
## $ feelrel <fct> very religious, NA, not rel or non, NA, NA, somwhat r...
## $ feeused <fct> "yes, money", "yes, money", "yes, money", "yes, money...
## $ fefam <fct> disagree, NA, disagree, disagree, NA, disagree, NA, N...
## $ fehire <fct> NA, NA, NA, agree, NA, strongly agree, NA, NA, NA, ne...
## $ fejobaff <fct> strongly against, NA, against, NA, NA, NA, NA, NA, st...
## $ fepol <fct> agree, NA, disagree, disagree, NA, disagree, NA, NA, ...
## $ fepresch <fct> strongly disagree, NA, disagree, disagree, NA, disagr...
## $ finalter <fct> better, worse, better, better, stayed same, worse, st...
## $ finrela <fct> below average, below average, above average, above av...
## $ firstyou <fct> NA, agree, NA, strongly agree, strongly agree, NA, di...
## $ fish <fct> NA, NA, NA, NA, does not have, NA, does not have, NA,...
## $ fishb4 <fct> NA, NA, NA, did not have, NA, NA, NA, NA, NA, NA, NA,...
## $ form <fct> standard <x>, alternate <y>, standard <x>, alternate ...
## $ formwt <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ fringeok <fct> somewhat true, NA, very true, not too true, NA, NA, s...
## $ frndsex <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ fucitzn <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ fund <fct> moderate, moderate, liberal, liberal, moderate, moder...
## $ fund16 <fct> fundamentalist, moderate, moderate, moderate, moderat...
## $ gender1 <fct> male, female, male, male, male, female, female, male,...
## $ gender10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ gender11 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ gender12 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ gender2 <fct> female, female, female, female, female, male, male, N...
## $ gender3 <fct> male, NA, male, NA, NA, NA, NA, NA, NA, female, NA, m...
## $ gender4 <fct> male, NA, female, NA, NA, NA, NA, NA, NA, NA, NA, mal...
## $ gender5 <fct> male, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ gender6 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ gender7 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ gender8 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ gender9 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ geneabrt2 <fct> no, no, NA, NA, no, no, yes, NA, NA, NA, yes, NA, yes...
## $ genegen <fct> somewhat dangerous, NA, NA, NA, NA, very dangerous, N...
## $ genegoo2 <fct> good > harm, harm > good, NA, NA, good > harm, good >...
## $ geneself2 <fct> no, no, NA, NA, no, yes, yes, NA, NA, NA, yes, NA, ye...
## $ genetics <fct> NA, somewhat likely, NA, somewhat likely, not at all ...
## $ genetst1 <fct> not very much, nothing at all, NA, NA, not very much,...
## $ getahead <fct> hard work, hard work, NA, NA, hard work, both equally...
## $ goat <fct> NA, NA, NA, NA, does not have, NA, does not have, NA,...
## $ goatb4 <fct> NA, NA, NA, did not have, NA, NA, NA, NA, NA, NA, NA,...
## $ god <fct> know god exists, know god exists, believe but doubts,...
## $ godchnge <fct> "believe now, didn't used to", NA, "don't believe now...
## $ godmeans <fct> disagree, NA, disagree, NA, NA, neither agree nor dis...
## $ godswill <fct> NA, somewhat likely, NA, not at all likely, not at al...
## $ goodlife <fct> NA, agree, agree, neither, agree, NA, disagree, stron...
## $ goveqinc <fct> NA, strongly disagree, NA, disagree, disagree, NA, ag...
## $ govlazy <fct> NA, agree, NA, disagree, agree, NA, neither agree nor...
## $ govvsrel <fct> strongly agree, NA, strongly agree, NA, NA, strongly ...
## $ granborn <fct> all in u.s, 4, 2, all in u.s, 2, all in u.s, 2, all i...
## $ grass <fct> NA, not legal, legal, not legal, not legal, NA, legal...
## $ gunlaw <fct> favor, favor, NA, NA, favor, favor, favor, favor, NA,...
## $ handmove <fct> no, NA, no, yes, NA, NA, no, yes, yes, yes, no, no, N...
## $ hapcohab <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, very happy, N...
## $ hapmar <fct> NA, NA, very happy, very happy, NA, NA, NA, NA, NA, p...
## $ happy <fct> pretty happy, very happy, very happy, very happy, pre...
## $ hapunhap <fct> fairly happy, NA, very happy, NA, NA, not very happy,...
## $ haveinfo <fct> somewhat true, NA, somewhat true, very true, NA, NA, ...
## $ health <fct> good, excellent, NA, NA, excellent, good, good, excel...
## $ health1 <fct> good, NA, very good, excellent, NA, NA, good, very go...
## $ healthissp <fct> good, very good, very good, excellent, excellent, goo...
## $ heaven <fct> "yes, definitely", NA, "yes, probably", NA, NA, "yes,...
## $ hefinfo <fct> 4th person, 1st person, 1st person, 1st person, 1st p...
## $ height <fct> 73, NA, 68, 68, NA, NA, 66, 66, 67, 69, 68, 62, NA, 7...
## $ hell <fct> "yes, definitely", NA, "yes, probably", NA, NA, "no, ...
## $ helpblk <fct> NA, govt help blks, agree with both, agree with both,...
## $ helpfrds <fct> NA, agree, NA, neither agree nor disagree, agree, NA,...
## $ helpful <fct> NA, helpful, helpful, helpful, helpful, NA, lookout f...
## $ helpnot <fct> NA, agree with both, govt does too much, 4, govt do m...
## $ helpoth <fct> NA, 2nd important, 3rd important, 3rd important, 2nd ...
## $ helppoor <fct> NA, agree with both, 4, 2, 4, NA, agree with both, go...
## $ helpsick <fct> NA, agree with both, agree with both, 2, agree with b...
## $ hhrace <fct> "other, mixed", "white", "other, mixed", "white", "wh...
## $ hhtype <fct> "4+adlts,0mar,0kids", "2adlts,ntmar,rel,0kids", "2adl...
## $ hhtype1 <fct> "unsure, no children", "other fam., no children", "ma...
## $ hindus <fct> neither positive nor negative, NA, somewhat positive,...
## $ hispanic <fct> not hispanic, not hispanic, chilean, not hispanic, no...
## $ hivtest <fct> NA, no, no, no, no, NA, NA, no, yes, yes, NA, yes, NA...
## $ hivtest1 <fct> NA, NA, NA, NA, NA, NA, NA, NA, 201598, 200307, NA, 2...
## $ hivtest2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, private doctor or hmo...
## $ hlpadvce <fct> NA, close family member, NA, close friend, no one, NA...
## $ hlpdown <fct> NA, close family member, NA, close friend, no one, NA...
## $ hlpequip <fct> somewhat true, NA, very true, somewhat true, NA, NA, ...
## $ hlphome <fct> NA, close family member, NA, close family member, som...
## $ hlpjob <fct> NA, no person or organization, NA, other organization...
## $ hlploan <fct> NA, public services, NA, private companies, other org...
## $ hlppaper <fct> NA, public services, NA, private companies, non-profi...
## $ hlpresde <fct> NA, no person or organization, NA, private companies,...
## $ hlpsick <fct> NA, close family member, NA, close family member, no ...
## $ hlpsickr <fct> NA, family members or close friends, NA, other organi...
## $ hlpsococ <fct> NA, close family member, NA, close friend, close frie...
## $ hlthdays <fct> 0, NA, 0, 0, NA, NA, 0, 0, 30, 10, 0, 0, NA, 0, NA, 0...
## $ hlthmntl <fct> very good, very good, very good, excellent, very good...
## $ hlthphys <fct> good, very good, good, excellent, excellent, good, go...
## $ hlthstrt <fct> NA, good, NA, good, good, good, good, NA, NA, good, e...
## $ homosex <fct> always wrong, not wrong at all, NA, NA, not wrong at ...
## $ homosex1 <fct> always wrong, NA, not wrong at all, NA, NA, not wrong...
## $ hompop <fct> 5, 2, 4, 2, 2, 2, 2, 1, 1, 2, 2, 4, 1, 3, 3, 2, 2, 4,...
## $ horse <fct> NA, NA, NA, NA, does not have, NA, does not have, NA,...
## $ horseb4 <fct> NA, NA, NA, did not have, NA, NA, NA, NA, NA, NA, NA,...
## $ hotcore <fct> true, NA, true, NA, NA, true, NA, NA, false, NA, true...
## $ hrs1 <fct> NA, NA, 40, 40, NA, NA, 35, 89+ hrs, 40, 40, 40, 20, ...
## $ hrs2 <fct> 41, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ hrsrelax <fct> 3, NA, 3, 7, NA, NA, 1, 1, 0, 4, 0, 5, NA, 24, NA, 5,...
## $ hsbio <fct> yes, NA, yes, NA, NA, yes, NA, NA, NA, NA, yes, NA, n...
## $ hschem <fct> yes, NA, yes, NA, NA, yes, NA, NA, NA, NA, yes, NA, n...
## $ hsmath <fct> "trigonometry linear programming analysis", NA, "pre-...
## $ hsphys <fct> no, NA, no, NA, NA, yes, NA, NA, NA, NA, no, NA, no, ...
## $ huadd <fct> yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes...
## $ huaddwhy <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ hubbywrk <fct> neither agree nor disagree, NA, strongly disagree, NA...
## $ huclean <fct> NA, clean, NA, clean, NA, clean, clean, so-so, dirty,...
## $ hunt <fct> neither, neither, NA, NA, neither, neither, neither, ...
## $ hunt1 <fct> neither hunts, neither hunts, NA, NA, neither hunts, ...
## $ hurtatwk <fct> 0, NA, 0, 0, NA, NA, 0, 0, 0, 0, 0, 0, NA, 0, NA, 0, ...
## $ hurtoth <fct> NA, not very likely, NA, not very likely, not likely ...
## $ hurtself <fct> NA, very likely, NA, somewhat likely, not likely at a...
## $ hvylift <fct> no, NA, no, yes, NA, NA, yes, yes, yes, no, no, no, N...
## $ hyperten <fct> yes, NA, yes, yes, NA, NA, no, no, yes, no, yes, no, ...
## $ id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16...
## $ idu30 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ if12who <fct> NA, NA, NA, NA, NA, NA, NA, obama, NA, obama, NA, NA,...
## $ if16who <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, clint...
## $ imbalnce <fct> NA, not very likely, NA, very likely, NA, NA, very li...
## $ imprvown <fct> NA, very likely, NA, not likely at all, somewhat like...
## $ imprvtrt <fct> NA, not likely at all, NA, very likely, not likely at...
## $ incgap <fct> NA, neither, NA, agree, disagree, NA, strongly agree,...
## $ incom16 <fct> below average, far below average, above average, abov...
## $ income <fct> NA, $25000 or more, $25000 or more, NA, NA, NA, $1500...
## $ income16 <fct> NA, $30000 to 34999, $150000 to $169999, $170000 or o...
## $ incuspop <fct> average, average, average, average, higher than avera...
## $ indperf <fct> yes, NA, yes, NA, NA, NA, NA, NA, NA, NA, yes, NA, NA...
## $ indus10 <fct> "employment services", "grocery stores", "wired telec...
## $ indusgen <fct> extremely dangerous, NA, NA, NA, NA, extremely danger...
## $ intage <fct> 68, 62, 68, 62, 68, 62, 46, 75, 46, 62, 62, 68, 68, 2...
## $ intcntct <fct> NA, none or almost none of it, NA, most of it, all or...
## $ intecon <fct> very interested, NA, very interested, NA, NA, very in...
## $ inteduc <fct> moderately interested, NA, very interested, NA, NA, m...
## $ intenvir <fct> very interested, NA, very interested, NA, NA, very in...
## $ intethn <fct> white, white, white, white, white, white, white, whit...
## $ intfarm <fct> moderately interested, NA, moderately interested, NA,...
## $ inthisp <fct> NA, not hispanic, NA, not hispanic, NA, not hispanic,...
## $ intid <fct> 125, 32, 125, 32, 125, 32, 101, 133, 101, 32, 32, 125...
## $ intintl <fct> moderately interested, NA, moderately interested, NA,...
## $ intlblks <fct> 4, NA, intelligent, 5, NA, 4, NA, NA, 4, 4, 4, 5, 4, ...
## $ intlhsps <fct> 4, NA, intelligent, 5, NA, 4, NA, NA, 4, 4, 4, 5, 4, ...
## $ intlwhts <fct> 4, NA, intelligent, 5, NA, 4, NA, NA, 4, 4, 4, 5, 5, ...
## $ intmed <fct> very interested, NA, very interested, NA, NA, very in...
## $ intmil <fct> moderately interested, NA, moderately interested, NA,...
## $ intrace1 <fct> NA, white, NA, white, NA, white, white, white, white,...
## $ intrace2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, w...
## $ intrace3 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ intsci <fct> very interested, NA, very interested, NA, NA, very in...
## $ intsex <fct> female, female, female, female, female, female, femal...
## $ intspace <fct> moderately interested, NA, moderately interested, NA,...
## $ inttech <fct> moderately interested, NA, very interested, NA, NA, v...
## $ intyrs <fct> 23, 21, 23, 21, 23, 21, 8, 6, 8, 21, 21, 23, 23, , , ...
## $ isco08 <fct> personnel and careers professionals, hand packers, co...
## $ isco88 <fct> 4190, 9322, 2131, 3133, 1232, 1231, 3231, 4131, 5131,...
## $ issp <fct> did issp, did issp, did issp, did issp, did issp, did...
## $ jew <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ jew16 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ jews <fct> somewhat negative, NA, somewhat positive, NA, NA, nei...
## $ jobfind <fct> very easy, NA, somewhat easy, not easy, NA, NA, NA, N...
## $ jobfind1 <fct> very easy to find similar job, NA, somewhat easy to f...
## $ joblose <fct> not likely, NA, not likely, not likely, NA, NA, NA, N...
## $ jobsecok <fct> somewhat true, NA, somewhat true, very true, NA, NA, ...
## $ kidpars <fct> NA, strongly agree, NA, agree, strongly agree, NA, ag...
## $ kidsinhh <fct> yes, no, yes, yes, yes, yes, no, no, no, yes, yes, ye...
## $ kidssol <fct> NA, much better, somewhat better, about the same, som...
## $ knowschd <fct> 4 weeks or more, NA, 4 weeks or more, between 3 and 4...
## $ knowwhat <fct> strongly agree, NA, agree, strongly agree, NA, NA, ag...
## $ knwbus <fct> NA, no one, NA, someone else i know, no one, NA, some...
## $ knwclenr <fct> NA, no one, NA, family or relative, no one, NA, someo...
## $ knwcop <fct> NA, no one, NA, family or relative, close friend, NA,...
## $ knwcuttr <fct> NA, no one, NA, family or relative, no one, NA, close...
## $ knwexec <fct> NA, no one, NA, no one, close friend, NA, no one, som...
## $ knwhrman <fct> NA, no one, NA, someone else i know, close friend, NA...
## $ knwlawyr <fct> NA, someone else i know, NA, family or relative, clos...
## $ knwmchnc <fct> NA, no one, NA, family or relative, no one, NA, close...
## $ knwmw1 <fct> NA, male, NA, male, female, NA, male, female, NA, mal...
## $ knwmw2 <fct> NA, female, NA, male, male, NA, female, NA, NA, male,...
## $ knwmw3 <fct> NA, NA, NA, female, male, NA, male, NA, NA, NA, NA, N...
## $ knwmw4 <fct> NA, NA, NA, female, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ knwmw5 <fct> NA, NA, NA, female, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ knwnurse <fct> NA, no one, NA, close friend, family or relative, NA,...
## $ knwtcher <fct> NA, no one, NA, family or relative, family or relativ...
## $ laidoff <fct> no, NA, no, no, NA, NA, no, no, no, no, no, no, NA, n...
## $ lasers <fct> false, NA, false, NA, NA, false, NA, NA, true, NA, fa...
## $ learnnew <fct> strongly agree, NA, agree, strongly agree, NA, NA, di...
## $ letdie1 <fct> no, NA, yes, no, NA, yes, NA, NA, yes, yes, yes, yes,...
## $ letin1a <fct> "remain the same as it is", NA, "reduced a little", "...
## $ libath <fct> not remove, not remove, NA, NA, not remove, not remov...
## $ libcom <fct> not remove, not remove, NA, NA, not remove, not remov...
## $ libhomo <fct> not remove, not remove, NA, NA, not remove, not remov...
## $ libmil <fct> not remove, not remove, NA, NA, not remove, not remov...
## $ libmslm <fct> not remove, not remove, NA, NA, not remove, not remov...
## $ librac <fct> not remove, not remove, NA, NA, not remove, not remov...
## $ life <fct> routine, exciting, NA, NA, routine, routine, routine,...
## $ lifein5 <fct> 9, NA, best possible state, 8, NA, NA, 8, 7, NA, 8, 9...
## $ lifenow <fct> 7, NA, 8, 8, NA, NA, 6, 7, 1, 7, 9, 6, NA, 6, NA, 7, ...
## $ liveblks <fct> neither favor nor oppose, NA, favor, neither favor no...
## $ lngthinv <fct> 136, 153, 90, 192, 111, 105, 111, 158, 159, 142, 132,...
## $ localnum <fct> "1-9", NA, "100-499", "1,000-1,999", NA, NA, "1-9", "...
## $ lonely1 <fct> NA, never, NA, rarely, rarely, NA, rarely, never, NA,...
## $ lonely2 <fct> NA, never, NA, rarely, never, NA, sometimes, never, N...
## $ lonely3 <fct> NA, never, NA, rarely, never, NA, rarely, never, NA, ...
## $ madeg <fct> high school, lt high school, bachelor, high school, h...
## $ madenkid <fct> "baptist, dk which", NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ maeduc <fct> 12, 8, 16, 12, 12, 12, 6, 12, 12, 20, 12, 14, 12, 12,...
## $ maind10 <fct> "clothing stores", "textile product mills, except car...
## $ maisco08 <fct> shop sales assistants, sewing machine operators, gene...
## $ maisco88 <fct> 5220, 8263, 4110, NA, 5131, 5122, 7200, 4131, 4222, 2...
## $ major1 <fct> communications/speech, NA, electronics, business admi...
## $ major2 <fct> NA, NA, NA, computer science, NA, NA, NA, NA, NA, NA,...
## $ majorcol <fct> communications/speech, NA, electronics, NA, NA, mathm...
## $ makefrnd <fct> disagree, NA, agree, NA, NA, agree, NA, NA, neither a...
## $ maleornt <fct> r sexual orientation uncertain, NA, NA, NA, r is not ...
## $ manvsemp <fct> very good, NA, quite good, quite good, NA, NA, very g...
## $ maocc10 <fct> "retail salespersons", "sewing machine operators", "o...
## $ mapres10 <fct> 31, 32, 32, NA, 35, 33, 44, 25, 38, 72, 64, 46, 31, 4...
## $ mapres105plus <fct> 18, 22, 26, NA, 28, 24, 47, 12, 29, 92, 87, 54, 16, 5...
## $ mar1 <fct> NA, married, NA, married, married, widowed, divorced,...
## $ mar11 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mar12 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mar2 <fct> NA, divorced, NA, married, married, never married, se...
## $ mar3 <fct> NA, NA, never married, NA, NA, NA, NA, NA, NA, never ...
## $ mar4 <fct> never married, NA, never married, NA, NA, NA, NA, NA,...
## $ mar5 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mar6 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mar7 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mar8 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mar9 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ marasian <fct> neither favor nor oppose, NA, strongly favor, neither...
## $ marblk <fct> oppose, NA, strongly favor, neither favor nor oppose,...
## $ marcohab <fct> "not married, no cohabitating partner", "not married,...
## $ marelkid <fct> "protestant", NA, "catholic", NA, NA, "catholic", NA,...
## $ marhisp <fct> neither favor nor oppose, NA, favor, neither favor no...
## $ marhomo <fct> strongly disagree, agree, NA, NA, strongly disagree, ...
## $ marital <fct> never married, separated, married, married, divorced,...
## $ martype <fct> NA, NA, marriage between a man and a woman, marriage ...
## $ marwht <fct> neither favor nor oppose, NA, favor, neither favor no...
## $ masei10 <fct> 39.7, 13.2, 35.8, NA, 21.8, 13.6, 25.1, 23.8, 25.7, 8...
## $ masei10educ <fct> 55.9, 16.5, 56.1, NA, 45.4, 22.3, 22, 33.7, 51.1, 99....
## $ masei10inc <fct> 30.9, 5.5, 22.8, NA, 6.9, 4.1, 24.7, 13.8, 9.4, 79.5,...
## $ matesex <fct> NA, NA, yes, NA, NA, NA, NA, NA, NA, yes, NA, yes, NA...
## $ mawrkgrw <fct> yes, yes, yes, no, yes, yes, yes, yes, yes, yes, yes,...
## $ mawrkslf <fct> someone else, someone else, someone else, NA, someone...
## $ mcsds1 <fct> NA, true, NA, false, true, NA, true, true, NA, true, ...
## $ mcsds2 <fct> NA, false, NA, true, true, NA, false, false, NA, fals...
## $ mcsds3 <fct> NA, true, NA, true, false, NA, false, true, NA, false...
## $ mcsds4 <fct> NA, false, NA, false, false, NA, false, false, NA, fa...
## $ mcsds5 <fct> NA, false, NA, false, true, NA, false, true, NA, fals...
## $ mcsds6 <fct> NA, false, NA, true, true, NA, false, false, NA, true...
## $ mcsds7 <fct> NA, false, NA, false, false, NA, false, true, NA, tru...
## $ meddoc <fct> NA, yes, NA, yes, yes, NA, yes, yes, NA, yes, NA, yes...
## $ mentldoc <fct> NA, yes, NA, yes, no, NA, yes, yes, NA, yes, NA, yes,...
## $ mentlhos <fct> NA, no, NA, yes, no, NA, yes, yes, NA, no, NA, yes, N...
## $ mentlill <fct> NA, not very likely, NA, very likely, not very likely...
## $ mentloth <fct> NA, yes, NA, yes, no, NA, yes, yes, NA, yes, NA, yes,...
## $ meovrwrk <fct> agree, NA, disagree, neither agree nor disagree, NA, ...
## $ mhdiagno <fct> NA, yes, NA, yes, yes, NA, yes, yes, NA, yes, NA, yes...
## $ mhp1r1 <fct> NA, spouse/partner (current/ex), NA, child, coworker,...
## $ mhp1r2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mhp2r1 <fct> NA, child, NA, other family, friend, NA, friend, NA, ...
## $ mhp2r2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mhp3r1 <fct> NA, NA, NA, other family, friend, NA, friend, NA, NA,...
## $ mhp3r2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mhp4r1 <fct> NA, NA, NA, friend, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mhp4r2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mhp5r1 <fct> NA, NA, NA, sibling, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ mhp5r2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mhtreat1 <fct> NA, yes, NA, no, unsure, NA, yes, no, NA, no, NA, yes...
## $ mhtreat2 <fct> NA, yes, NA, unsure, unsure, NA, yes, NA, NA, no, NA,...
## $ mhtreat3 <fct> NA, NA, NA, no, no, NA, yes, NA, NA, NA, NA, NA, NA, ...
## $ mhtreat4 <fct> NA, NA, NA, no, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mhtreat5 <fct> NA, NA, NA, unsure, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mhtreatd <fct> NA, NA, NA, yes, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ mhunsure <fct> NA, "disagree, or", NA, "disagree, or", "disagree, or...
## $ miracles <fct> "yes, definitely", NA, "yes, probably", NA, NA, "yes,...
## $ misswork <fct> 0, NA, 0, 0, NA, NA, 0, 0, 0, 4, 0, 0, NA, 0, NA, 0, ...
## $ mnthsusa <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ mntlhlth <fct> 20, NA, 3, 1, NA, NA, 0, 1, 10, 10, 0, 0, NA, 0, NA, ...
## $ mobile16 <fct> "different state", "different state", "different stat...
## $ mode <fct> over the phone, in-person, in-person, in-person, over...
## $ moredays <fct> 8, NA, 3, 2, NA, NA, 1, 24, 0, 3, 2, 6, NA, 0, NA, 0,...
## $ muslims <fct> somewhat negative, NA, somewhat positive, NA, NA, nei...
## $ mustdoc <fct> NA, yes, NA, no, no, NA, yes, yes, NA, yes, NA, yes, ...
## $ musthosp <fct> NA, yes, NA, no, no, NA, yes, yes, NA, yes, NA, yes, ...
## $ mustmed <fct> NA, yes, NA, no, no, NA, yes, yes, NA, yes, NA, no, N...
## $ mustwork <fct> no, NA, no, yes, NA, NA, yes, yes, no, yes, yes, no, ...
## $ mygoals <fct> NA, completely true, NA, mostly true, mostly true, NA...
## $ myprobs1 <fct> NA, 8, NA, 2, not at all, NA, 3, 7, NA, 4, NA, very m...
## $ myprobs2 <fct> NA, very much, NA, not at all, not at all, NA, not at...
## $ myprobs3 <fct> NA, NA, NA, not at all, 5, NA, not at all, NA, NA, NA...
## $ myprobs4 <fct> NA, NA, NA, not at all, NA, NA, NA, NA, NA, NA, NA, N...
## $ myprobs5 <fct> NA, NA, NA, not at all, NA, NA, NA, NA, NA, NA, NA, N...
## $ myskills <fct> strongly agree, NA, agree, strongly agree, NA, NA, ag...
## $ mywaygod <fct> agree, NA, agree, NA, NA, agree, NA, NA, strongly agr...
## $ nanoben <fct> slightly in favor, NA, NA, NA, NA, slightly in favor,...
## $ nanoharm <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, stron...
## $ nanowill <fct> benefits greater, NA, NA, NA, NA, benefits greater, N...
## $ nataccess <fct> NA, strongly agree, NA, strongly agree, strongly agre...
## $ natactive <fct> NA, strongly agree, NA, strongly agree, strongly agre...
## $ nataid <fct> too much, NA, NA, NA, NA, NA, NA, about right, too mu...
## $ nataidy <fct> NA, too much, NA, too much, about right, too much, to...
## $ natarms <fct> too much, NA, too little, NA, NA, NA, NA, too little,...
## $ natarmsy <fct> NA, too little, NA, too much, too little, about right...
## $ natchld <fct> about right, about right, NA, too little, about right...
## $ natcity <fct> too little, NA, about right, NA, NA, NA, NA, too much...
## $ natcityy <fct> NA, about right, NA, about right, about right, about ...
## $ natcrime <fct> too little, NA, NA, NA, NA, NA, NA, too little, too l...
## $ natcrimy <fct> NA, too little, NA, too little, too little, about rig...
## $ natdrug <fct> too little, NA, too little, NA, NA, NA, NA, too littl...
## $ natdrugy <fct> NA, too little, NA, too little, too little, too littl...
## $ nateduc <fct> too little, NA, too little, NA, NA, NA, NA, too littl...
## $ nateducy <fct> NA, too little, NA, about right, about right, about r...
## $ natenrgy <fct> too little, about right, too little, too little, too ...
## $ natenvir <fct> about right, NA, too little, NA, NA, NA, NA, too litt...
## $ natenviy <fct> NA, too little, NA, too little, too little, too littl...
## $ natfare <fct> about right, NA, too little, NA, NA, NA, NA, too much...
## $ natfarey <fct> NA, too little, NA, too little, about right, too litt...
## $ natheal <fct> too little, NA, too little, NA, NA, NA, NA, too littl...
## $ nathealy <fct> NA, about right, NA, about right, too little, too lit...
## $ natlack <fct> NA, somewhat disagree, NA, strongly disagree, strongl...
## $ natmass <fct> about right, about right, too little, about right, to...
## $ natmeet <fct> NA, strongly agree, NA, strongly agree, strongly agre...
## $ natnotice <fct> NA, strongly agree, NA, strongly agree, strongly agre...
## $ natpark <fct> too much, about right, about right, about right, too ...
## $ natrace <fct> too little, NA, too little, NA, NA, NA, NA, about rig...
## $ natracey <fct> NA, about right, NA, too little, too much, about righ...
## $ natrelax <fct> NA, strongly agree, NA, strongly agree, strongly agre...
## $ natroad <fct> too little, about right, too little, too little, too ...
## $ natsat <fct> NA, strongly agree, NA, strongly agree, strongly agre...
## $ natsci <fct> about right, too little, NA, too little, too little, ...
## $ natsoc <fct> too little, too little, NA, too much, about right, to...
## $ natspac <fct> too much, NA, too little, NA, NA, NA, NA, too little,...
## $ natspacy <fct> NA, about right, NA, about right, too little, about r...
## $ nattime <fct> NA, strongly agree, NA, strongly agree, strongly agre...
## $ nattimeok <fct> NA, strongly agree, NA, somewhat agree, strongly agre...
## $ natviews <fct> NA, strongly agree, NA, strongly agree, strongly agre...
## $ neisafe <fct> very safe, very safe, very safe, very safe, very safe...
## $ newfrds <fct> NA, NA, NA, rarely, rarely, NA, sometimes, NA, NA, ra...
## $ news <fct> less than once wk, NA, never, everyday, NA, everyday,...
## $ newsfrom <fct> the internet, NA, radio, NA, NA, tv, NA, NA, tv, NA, ...
## $ nextgen <fct> strongly agree, NA, agree, NA, NA, strongly agree, NA...
## $ nihilism <fct> strongly disagree, NA, strongly disagree, NA, NA, dis...
## $ notsmart <fct> never, never, NA, NA, never, a few times a month, a f...
## $ ntwkhard <fct> 10, NA, 30, 10, NA, NA, 0, 10, 0, 50, 100, 20, NA, 2,...
## $ nukegen <fct> extremely dangerous, NA, NA, NA, NA, somewhat dangero...
## $ numcong <fct> 300, NA, 1000, 100, 2400, 1200, 35, 2000, NA, NA, NA,...
## $ numemps <fct> NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA...
## $ numlangs <fct> NA, one language, NA, one language, one language, NA,...
## $ nummen <fct> NA, 56, 0, 15, 0, NA, NA, 5, 9, 4, NA, 1, NA, 0, 2, N...
## $ numorg <fct> NA, NA, 5000, 1000-1999 in range, NA, NA, 2, 1000, 1,...
## $ numpets <fct> NA, no pets, NA, no pets, 1, NA, 1, no pets, NA, 1, N...
## $ numwomen <fct> NA, 0, 8, 0, 3, NA, NA, 5, 0, 4, NA, 0, NA, 5, 0, NA,...
## $ obey <fct> NA, 4th important, least important, least important, ...
## $ occ10 <fct> "human resources workers", "packers and packagers, ha...
## $ odds1 <fct> no, NA, no, NA, NA, no, NA, NA, no, NA, no, NA, no, N...
## $ odds2 <fct> yes, NA, yes, NA, NA, yes, NA, NA, yes, NA, yes, NA, ...
## $ old1 <fct> NA, 74, NA, 58, 71, 66, 58, NA, 62, 54, 53, 33, 60, 3...
## $ old10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ old11 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ old12 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ old2 <fct> NA, 53, NA, 63, 67, 34, 40, NA, NA, 50, 58, 12, NA, 4...
## $ old3 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, 18, NA, 7, NA, 7,...
## $ old4 <fct> 43, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA...
## $ old5 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ old6 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ old7 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ old8 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ old9 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ opdevel <fct> somewhat true, NA, somewhat true, somewhat true, NA, ...
## $ otcmed <fct> NA, yes, NA, no, no, NA, no, no, NA, no, NA, yes, NA,...
## $ oth16 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 7...
## $ other <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, "congregationalis...
## $ othersex <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ othlang <fct> yes, no, no, no, no, no, yes, no, no, no, yes, no, no...
## $ othlang1 <fct> spanish, NA, NA, NA, NA, NA, spanish, NA, NA, NA, fre...
## $ othlang2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ othmhneg <fct> NA, somewhat, NA, somewhat, not at all, NA, not very ...
## $ othpet <fct> NA, NA, NA, NA, does not have, NA, does not have, NA,...
## $ othpetb4 <fct> NA, NA, NA, did not have, NA, NA, NA, NA, NA, NA, NA,...
## $ oversamp <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ overwork <fct> agree, NA, agree, disagree, NA, NA, disagree, agree, ...
## $ owngun <fct> no, no, NA, NA, yes, yes, no, no, NA, NA, yes, NA, no...
## $ ownstock <fct> "i do not know if i own stock in my company", NA, "ye...
## $ padeg <fct> high school, lt high school, high school, bachelor, h...
## $ padenkid <fct> "christian; central christian", NA, NA, NA, NA, NA, N...
## $ paeduc <fct> 12, 0, 12, 16, 12, 12, NA, NA, 12, 6, 12, NA, NA, 16,...
## $ paidsex <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ painarms <fct> no, NA, no, no, NA, NA, no, no, yes, yes, no, no, NA,...
## $ paind10 <fct> "postal service", "construction", "waste management a...
## $ paisco08 <fct> "mail carriers and sorting clerks", "bricklayers and ...
## $ paisco88 <fct> 4142, 7122, 1210, 1319, 4142, 4142, NA, NA, 1226, 712...
## $ paocc10 <fct> "postal service mail carriers", "brickmasons, blockma...
## $ papres10 <fct> 45, 39, 72, 39, 45, 45, NA, NA, 45, 44, 46, NA, 32, 2...
## $ papres105plus <fct> 51, 36, 90, 42, 51, 51, NA, NA, 50, 49, 54, NA, 20, 1...
## $ parborn <fct> both in u.s, mother only, father only, both in u.s, f...
## $ parelkid <fct> "protestant", NA, "catholic", NA, NA, "catholic", NA,...
## $ parsol <fct> NA, much better, about the same, somewhat better, muc...
## $ partfull <fct> full-time, NA, full-time, full-time, NA, NA, full-tim...
## $ partlsc <fct> NA, several times a year, NA, several times a year, n...
## $ partners <fct> NA, no partners, 1 partner, no partners, no partners,...
## $ partnrs5 <fct> NA, "1 partner", "1 partner", "no partners", "no part...
## $ partpart <fct> NA, never, NA, never, never, NA, never, never, NA, ne...
## $ partteam <fct> "no, i work mostly on my own", NA, "yes, i work as pa...
## $ partvol <fct> NA, never, NA, several times a year, several times a ...
## $ partyid <fct> "not str republican", "ind,near dem", "ind,near rep",...
## $ pasei10 <fct> 58.4, 24.6, 77.4, 67.7, 58.4, 58.4, NA, NA, 46.6, 28....
## $ pasei10educ <fct> 50.1, 16, 85.7, 76.9, 50.1, 50.1, NA, NA, 47.3, 25.7,...
## $ pasei10inc <fct> 78.4, 30.4, 87, 76.8, 78.4, 78.4, NA, NA, 55.3, 30.3,...
## $ pawrkslf <fct> someone else, someone else, self-employed, someone el...
## $ petb4 <fct> NA, no, NA, yes, yes, NA, yes, no, NA, yes, NA, no, N...
## $ petb4cmfrt <fct> NA, NA, NA, often, NA, NA, NA, NA, NA, NA, NA, NA, NA...
## $ petb4fam <fct> NA, NA, NA, almost always, NA, NA, NA, NA, NA, NA, NA...
## $ petb4ply <fct> NA, NA, NA, almost always, NA, NA, NA, NA, NA, NA, NA...
## $ petcmfrt <fct> NA, NA, NA, NA, never, NA, almost always, NA, NA, oft...
## $ petfam <fct> NA, NA, NA, NA, never, NA, almost always, NA, NA, alm...
## $ petplay <fct> NA, NA, NA, NA, sometimes, NA, almost always, NA, NA,...
## $ phase <fct> phase two - sub sampled cases, phase one - initial ca...
## $ phone <fct> cellphone, phone in home, phone in home, phone in hom...
## $ phyeffrt <fct> very light, NA, very light, somewhat hard, NA, NA, ha...
## $ physacts <fct> completely, moderately, completely, completely, compl...
## $ physhlth <fct> 0, NA, 0, 0, NA, NA, 0, 0, 30, 1, 0, 0, NA, 0, NA, 0,...
## $ physill <fct> NA, somewhat likely, NA, somewhat likely, not at all ...
## $ pig <fct> NA, NA, NA, NA, does not have, NA, does not have, NA,...
## $ pigb4 <fct> NA, NA, NA, did not have, NA, NA, NA, NA, NA, NA, NA,...
## $ pikupsex <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ pilingup <fct> NA, never, NA, rarely, never, NA, sometimes, rarely, ...
## $ pillok <fct> disagree, NA, disagree, agree, NA, agree, NA, NA, agr...
## $ pistol <fct> no, no, NA, NA, yes, no, no, no, NA, NA, no, NA, no, ...
## $ polabuse <fct> NA, no, no, no, no, NA, no, no, no, no, NA, no, NA, n...
## $ polattak <fct> NA, no, yes, yes, yes, NA, yes, yes, NA, yes, NA, yes...
## $ poleff11 <fct> NA, disagree, NA, agree, disagree, NA, agree, disagre...
## $ polescap <fct> NA, yes, yes, yes, yes, NA, no, no, yes, yes, NA, no,...
## $ polhitok <fct> NA, no, no, yes, yes, NA, yes, no, no, yes, NA, no, N...
## $ polmurdr <fct> NA, yes, no, no, no, NA, no, yes, no, no, NA, no, NA,...
## $ polviews <fct> conservative, NA, slghtly conservative, moderate, ext...
## $ poorserv <fct> NA, never, NA, NA, never, a few times a year, a few t...
## $ popespks <fct> NA, certainly true, NA, NA, probably true, probably t...
## $ popular <fct> NA, least important, 4th important, 4th important, le...
## $ pornlaw <fct> NA, illegal under 18, illegal under 18, illegal under...
## $ posslq <fct> no steady partner, NA, married with partner, NA, NA, ...
## $ posslqy <fct> NA, "i have a husband or wife or steady partner, but ...
## $ postlife <fct> yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes...
## $ pray <fct> several times a week, once a day, lt once a week, sev...
## $ prayer <fct> disapprove, NA, approve, approve, NA, approve, NA, NA...
## $ prayfreq <fct> several times a week, NA, 2-3 times a month, NA, NA, ...
## $ premarsx <fct> not wrong at all, NA, not wrong at all, sometimes wro...
## $ pres12 <fct> romney, obama, romney, romney, romney, obama, obama, ...
## $ pres16 <fct> trump, trump, trump, don't know, trump, clinton, clin...
## $ prestg10 <fct> 47, 22, 61, 59, 53, 53, 48, 35, 35, 39, 72, 35, 45, 7...
## $ prestg105plus <fct> 59, 13, 92, 79, 73, 65, 50, 27, 28, 34, 90, 27, 46, 9...
## $ preteen <fct> 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 1, 0, 0, 0, 0...
## $ prodctiv <fct> disagree, NA, agree, agree, NA, NA, agree, agree, agr...
## $ promtefr <fct> somewhat true, NA, not too true, not too true, NA, NA...
## $ promteok <fct> somewhat true, NA, somewhat true, not at all true, NA...
## $ proudemp <fct> strongly agree, NA, agree, strongly agree, NA, NA, ag...
## $ prvdhlth <fct> NA, "government", NA, "private companies/for-profit o...
## $ prvdold <fct> NA, "government", NA, "non-profit organizations/chari...
## $ quallife <fct> good, excellent, excellent, excellent, very good, fai...
## $ racdif1 <fct> no, NA, yes, yes, NA, yes, NA, NA, yes, yes, no, no, ...
## $ racdif2 <fct> no, NA, no, no, NA, no, NA, NA, no, no, no, no, yes, ...
## $ racdif3 <fct> no, NA, yes, yes, NA, yes, NA, NA, yes, yes, no, yes,...
## $ racdif4 <fct> yes, NA, no, no, NA, no, NA, NA, no, no, no, yes, yes...
## $ race <fct> white, white, white, white, black, white, black, whit...
## $ racecen1 <fct> white, white, white, white, black or african american...
## $ racecen2 <fct> NA, NA, NA, NA, white, NA, NA, american indian or ala...
## $ racecen3 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ raclive <fct> no, NA, no, no, yes, yes, yes, NA, yes, yes, yes, yes...
## $ racopen <fct> owner decides, cant discriminate, NA, NA, cant discri...
## $ racwork <fct> all white, NA, NA, NA, NA, NA, half white-black, half...
## $ radioact <fct> false, NA, false, NA, NA, false, NA, NA, false, NA, f...
## $ random <fct> 2, NA, 1, NA, NA, NA, NA, 2, 2, NA, NA, NA, 2, NA, 2,...
## $ rank <fct> 4, top, 5, 4, 5, 5, 7, 5, 9, 3, 3, 5, bottom, 7, 5, 5...
## $ ratepain <fct> 1, 7, 2, 2, no pain, 1, 1, no pain, 9, 4, no pain, no...
## $ ratetone <fct> NA, lightest, NA, lightest, NA, lightest, 8, 3, 8, li...
## $ realinc <fct> NA, 14755, 72640, 119879.41732, 119879.41732, NA, 851...
## $ realrinc <fct> NA, NA, 45400, 54480, NA, NA, 8512.5, 17025, 908, 454...
## $ reborn <fct> yes, no, no, no, no, no, yes, no, no, no, no, yes, no...
## $ reg16 <fct> middle atlantic, middle atlantic, middle atlantic, mi...
## $ region <fct> new england, new england, new england, new england, n...
## $ relactiv <fct> several times a year, never, less than once a year, n...
## $ relate1 <fct> head of household, head of household, head of househo...
## $ relate10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relate11 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relate12 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relate2 <fct> non-relative, child, spouse, spouse, spouse, child, c...
## $ relate3 <fct> non-relative, NA, child, NA, NA, NA, NA, NA, NA, chil...
## $ relate4 <fct> non-relative, NA, child, NA, NA, NA, NA, NA, NA, NA, ...
## $ relate5 <fct> non-relative, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ relate6 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relate7 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relate8 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relate9 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relatsex <fct> NA, "no, no relationship", "yes, in relationship", "y...
## $ relext1 <fct> definitely not, NA, probably, NA, NA, probably, NA, N...
## $ relext3 <fct> probably not, NA, probably, NA, NA, probably, NA, NA,...
## $ relgenbar <fct> disagree, NA, agree, NA, NA, neither agree nor disagr...
## $ relgeneq <fct> treats women better than men, NA, treats women better...
## $ relhh1 <fct> householder, householder, householder, householder, h...
## $ relhh10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhh11 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhh12 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhh2 <fct> "partner,girl(boy)friend", "child, unsp", "spouse", "...
## $ relhh3 <fct> "roommate, housemate", NA, "child, unsp", NA, NA, NA,...
## $ relhh4 <fct> "roommate, housemate", NA, "child, unsp", NA, NA, NA,...
## $ relhh5 <fct> "roommate, housemate", NA, NA, NA, NA, NA, NA, NA, NA...
## $ relhh6 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhh7 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhh8 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhh9 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhhd1 <fct> head of household, head of household, head of househo...
## $ relhhd10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhhd11 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhhd12 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhhd2 <fct> "partner,fiance-e-,boyfriend,girlfriend,etc", "child,...
## $ relhhd3 <fct> "roommate,housemate", NA, "child,natural or adopted,s...
## $ relhhd4 <fct> "roommate,housemate", NA, "child,natural or adopted,s...
## $ relhhd5 <fct> "roommate,housemate", NA, NA, NA, NA, NA, NA, NA, NA,...
## $ relhhd6 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhhd7 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhhd8 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relhhd9 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relig <fct> christian, catholic, none, protestant, catholic, cath...
## $ relig16 <fct> protestant, catholic, catholic, catholic, catholic, c...
## $ religcon <fct> agree, NA, not agree/dsagre, NA, NA, agree, NA, NA, d...
## $ religint <fct> strongly agree, NA, agree, NA, NA, agree, NA, NA, not...
## $ religkid <fct> "protestant", NA, "catholic", NA, NA, "catholic", NA,...
## $ reliten <fct> strong, strong, no religion, strong, strong, not very...
## $ relmarry <fct> probably not accept, NA, probably accept, NA, NA, def...
## $ relobjct <fct> yes, NA, no, NA, NA, yes, NA, NA, yes, NA, yes, NA, y...
## $ relpast <fct> strongly disagree, NA, neither agree nor disagree, NA...
## $ relpersn <fct> very religious, modrte religious, slight religious, s...
## $ relrlvnt <fct> strongly agree, NA, disagree, NA, NA, agree, NA, NA, ...
## $ relscrpt <fct> yes, NA, no, NA, NA, yes, NA, NA, no, NA, no, NA, yes...
## $ relsp1 <fct> "spouse", NA, "spouse", "spouse", "spouse", NA, NA, N...
## $ relsp10 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relsp11 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relsp12 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relsp2 <fct> "hh spouse, partner", NA, "hh spouse, partner", "hh s...
## $ relsp3 <fct> "roommate, housemate", NA, "child, not specified", NA...
## $ relsp4 <fct> "roommate, housemate", NA, "child, not specified", NA...
## $ relsp5 <fct> "roommate, housemate", NA, NA, NA, NA, NA, NA, NA, NA...
## $ relsp6 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relsp7 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relsp8 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relsp9 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ relsprt <fct> "i follow a religion and consider myself to be a spir...
## $ reptile <fct> NA, NA, NA, NA, has, NA, does not have, NA, NA, does ...
## $ reptileb4 <fct> NA, NA, NA, did not have, NA, NA, NA, NA, NA, NA, NA,...
## $ res16 <fct> town lt 50000, 50000 to 250000, big-city suburb, town...
## $ respect <fct> strongly agree, NA, agree, strongly agree, NA, NA, ag...
## $ respnum <fct> 4th person, 1st person, 2nd person, 2nd person, 1st p...
## $ respond <fct> high, high, high, high, high, high, high, high, low, ...
## $ rfamlook <fct> iap, iap, iap, iap, iap, iap, iap, iap, iap, iap, iap...
## $ rgroomed <fct> NA, about average, NA, about average, NA, well groome...
## $ rhlthend <fct> NA, NA, NA, NA, NA, NA, NA, excellent, poor, NA, NA, ...
## $ richwork <fct> continue working, NA, NA, NA, NA, NA, continue workin...
## $ rifle <fct> no, no, NA, NA, no, yes, no, no, NA, NA, no, NA, no, ...
## $ rincblls <fct> yes, NA, yes, yes, NA, NA, yes, no, no, yes, yes, no,...
## $ rincom16 <fct> NA, NA, $90000 to $109999, $110000 to $129999, NA, NA...
## $ rincome <fct> NA, NA, $25000 or more, $25000 or more, NA, NA, $1500...
## $ rlooks <fct> NA, about average, NA, attractive, NA, attractive, ab...
## $ rowngun <fct> NA, NA, NA, NA, yes, no, NA, NA, NA, NA, yes, NA, NA,...
## $ rplace <fct> non-relative, head of household, spouse, spouse, head...
## $ rvisitor <fct> r. is household member, r. is household member, r. is...
## $ rweight <fct> NA, slightly overweight, NA, about the right weight, ...
## $ rxmed <fct> NA, yes, NA, yes, no, NA, yes, yes, NA, yes, NA, no, ...
## $ safefrst <fct> strongly agree, NA, agree, strongly agree, NA, NA, ag...
## $ safehlth <fct> strongly agree, NA, agree, strongly agree, NA, NA, ag...
## $ safetywk <fct> strongly agree, NA, agree, agree, NA, NA, agree, agre...
## $ sampcode <fct> 601, 601, 601, 601, 601, 601, 601, 601, 601, 601, 601...
## $ sample <fct> 2010 fp, 2010 fp, 2010 fp, 2010 fp, 2010 fp, 2010 fp,...
## $ satfam7 <fct> fairly satisfied, NA, fairly satisfied, NA, NA, neith...
## $ satfin <fct> not at all sat, more or less, more or less, satisfied...
## $ satjob <fct> very satisfied, NA, mod. satisfied, very satisfied, N...
## $ satjob1 <fct> somewhat satisfied, NA, somewhat satisfied, very sati...
## $ satlife <fct> NA, completely satisfied, NA, mostly satisfied, mostl...
## $ satsoc <fct> good, very good, very good, good, excellent, fair, go...
## $ savesoul <fct> yes, yes, no, yes, yes, no, yes, no, no, no, no, yes,...
## $ scibnfts <fct> harmful results greater, NA, benefits greater, NA, NA...
## $ scientbe <fct> agree, NA, agree, NA, NA, agree, NA, NA, strongly agr...
## $ scientgo <fct> strongly agree, NA, agree, NA, NA, strongly agree, NA...
## $ scienthe <fct> agree, NA, agree, NA, NA, agree, NA, NA, disagree, NA...
## $ scientod <fct> agree, NA, disagree, NA, NA, disagree, NA, NA, disagr...
## $ scifrom <fct> the internet, NA, books other printed material, NA, N...
## $ scinews1 <fct> NA, NA, NA, NA, NA, printed newspapers, NA, NA, NA, N...
## $ scinews2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ scinews3 <fct> "science site", NA, NA, NA, NA, NA, NA, NA, "online n...
## $ scistudy <fct> little understanding, NA, general sense, NA, NA, clea...
## $ scitext <fct> NA, NA, measurement, NA, NA, rigorous systematic comp...
## $ secondwk <fct> no, NA, no, no, NA, NA, no, yes, no, no, no, no, NA, ...
## $ seeksci <fct> the internet, NA, the internet, NA, NA, tv, NA, NA, t...
## $ seetalk1 <fct> NA, very often, NA, 7, not at all, NA, very often, 4,...
## $ seetalk2 <fct> NA, not at all, NA, 2, not at all, NA, not at all, NA...
## $ seetalk3 <fct> NA, NA, NA, 7, 5, NA, not at all, NA, NA, NA, NA, NA,...
## $ seetalk4 <fct> NA, NA, NA, 6, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
## $ seetalk5 <fct> NA, NA, NA, not at all, NA, NA, NA, NA, NA, NA, NA, N...
## $ sei10 <fct> 65.3, 14.8, 83.4, 69.3, 68.6, 69.3, 24.2, 23.7, 21.8,...
## $ sei10educ <fct> 82.4, 16.5, 89.4, 86.7, 79.2, 82.8, 40.8, 31.9, 45.4,...
## $ sei10inc <fct> 65, 7.8, 93.1, 68.4, 76.4, 74, 11.3, 14.5, 6.9, 82.7,...
## $ selfhelp <fct> NA, yes, NA, yes, no, NA, yes, yes, NA, yes, NA, yes,...
## $ seriousp <fct> NA, very serious, NA, very serious, somewhat serious,...
## $ severe1 <fct> NA, very severe, NA, not at all severe, very severe, ...
## $ severe2 <fct> NA, very severe, NA, 8, very severe, NA, 9, NA, NA, 8...
## $ severe3 <fct> NA, NA, NA, 2, 5, NA, 2, NA, NA, NA, NA, NA, NA, NA, ...
## $ severe4 <fct> NA, NA, NA, not at all severe, NA, NA, NA, NA, NA, NA...
## $ severe5 <fct> NA, NA, NA, 9, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
## $ sex <fct> male, female, male, female, male, female, female, mal...
## $ sexbirth <fct> NA, female, male, female, male, NA, NA, male, female,...
## $ sexeduc <fct> favor, NA, oppose, favor, NA, favor, NA, NA, favor, f...
## $ sexfreq <fct> NA, not at all, weekly, not at all, not at all, NA, N...
## $ sexnow <fct> NA, women, man, women, man, NA, NA, man, women, man, ...
## $ sexornt <fct> NA, heterosexual or straight, heterosexual or straigh...
## $ sexsex <fct> NA, NA, exclusively female, NA, NA, NA, NA, NA, NA, e...
## $ sexsex5 <fct> NA, exclusively male, exclusively female, NA, NA, NA,...
## $ shotgun <fct> no, no, NA, NA, yes, no, no, no, NA, NA, yes, NA, no,...
## $ sibs <fct> 4, 4, 2, 3, 3, 1, 7, 2, 4, 2, 3, 2, 9, 6, 4, 1, 1, 3,...
## $ size <fct> 14, 14, 14, 14, 14, 14, 24, 24, 24, 56, 56, 56, 56, 1...
## $ slfmangd <fct> no, NA, no, yes, NA, NA, no, no, NA, no, no, no, NA, ...
## $ slpprblm <fct> sometimes, NA, sometimes, sometimes, NA, NA, rarely, ...
## $ smallgap <fct> NA, disagree, NA, disagree, disagree, NA, strongly ag...
## $ smammal <fct> NA, NA, NA, NA, does not have, NA, does not have, NA,...
## $ smammalb4 <fct> NA, NA, NA, did not have, NA, NA, NA, NA, NA, NA, NA,...
## $ socbar <fct> once a month, NA, once a year, once a year, NA, once ...
## $ socfrend <fct> sev times a mnth, NA, once a month, once a month, NA,...
## $ socommun <fct> never_(7), NA, sev times a mnth, never_(7), NA, sev t...
## $ socrel <fct> sev times a year, NA, almost daily, almost daily, NA,...
## $ solarrev <fct> one year, NA, one year, NA, NA, one year, NA, NA, one...
## $ spaneng <fct> english, english, english, english, english, english,...
## $ spanint <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ spanking <fct> agree, NA, agree, disagree, NA, disagree, NA, NA, str...
## $ spanself <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ spdeg <fct> NA, NA, junior college, junior college, NA, NA, NA, N...
## $ spden <fct> NA, NA, NA, united methodist, NA, NA, NA, NA, NA, NA,...
## $ speduc <fct> NA, NA, 14, 14, NA, NA, NA, NA, NA, 11, NA, NA, NA, 1...
## $ spevwork <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, yes, NA, NA, NA, ...
## $ spfalook <fct> iap, iap, iap, iap, iap, iap, iap, iap, iap, iap, iap...
## $ spfund <fct> NA, NA, moderate, liberal, NA, NA, NA, NA, NA, modera...
## $ sphealer <fct> NA, yes, NA, no, no, NA, no, no, NA, no, NA, yes, NA,...
## $ sphrs1 <fct> NA, NA, 40, 40, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ sphrs2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ spind10 <fct> NA, NA, "pharmaceutical and medicine manufacturing", ...
## $ spisco08 <fct> NA, NA, "agricultural technicians", "medical imaging ...
## $ spisco88 <fct> NA, NA, 3212, 3133, NA, NA, NA, NA, NA, 4211, 9140, N...
## $ spjew <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ spkath <fct> allowed, allowed, NA, NA, allowed, allowed, allowed, ...
## $ spkcom <fct> allowed, allowed, NA, NA, allowed, allowed, not allow...
## $ spkhomo <fct> allowed, allowed, NA, NA, allowed, allowed, allowed, ...
## $ spklang <fct> well, NA, NA, NA, NA, NA, not well, NA, NA, NA, poorl...
## $ spkmil <fct> allowed, not allowed, NA, NA, allowed, allowed, allow...
## $ spkmslm <fct> "yes, allowed", "yes, allowed", NA, NA, "yes, allowed...
## $ spkrac <fct> allowed, allowed, NA, NA, allowed, allowed, allowed, ...
## $ splive <fct> iap, iap, iap, iap, iap, iap, iap, iap, iap, iap, iap...
## $ spocc10 <fct> NA, NA, agricultural and food science technicians, di...
## $ spother <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 7...
## $ sppres10 <fct> NA, NA, 45, 59, NA, NA, NA, NA, NA, 28, 24, NA, NA, 5...
## $ sppres105plus <fct> NA, NA, 50, 79, NA, NA, NA, NA, NA, 16, 15, NA, NA, 7...
## $ sprel <fct> NA, NA, catholic, protestant, NA, NA, NA, NA, NA, cat...
## $ sprtprsn <fct> very spiritual, very spiritual, modeate spirtual, mod...
## $ spsei10 <fct> NA, NA, 44.5, 69.3, NA, NA, NA, NA, NA, 21.6, 20.7, N...
## $ spsei10educ <fct> NA, NA, 55.6, 86.7, NA, NA, NA, NA, NA, 35, 22.3, NA,...
## $ spsei10inc <fct> NA, NA, 42.5, 68.4, NA, NA, NA, NA, NA, 9.9, 14.7, NA...
## $ spvtrfair <fct> very true, NA, somewhat true, very true, NA, NA, some...
## $ spwksup <fct> NA, NA, no, no, NA, NA, NA, NA, NA, NA, yes, NA, NA, ...
## $ spwrkslf <fct> NA, NA, someone else, someone else, NA, NA, NA, NA, N...
## $ spwrksta <fct> NA, NA, working fulltime, working fulltime, NA, NA, N...
## $ srcbelt <fct> "suburb, 13-100", "suburb, 13-100", "suburb, 13-100",...
## $ stockops <fct> no, NA, no, NA, NA, NA, no, yes, NA, no, NA, NA, NA, ...
## $ stockval <fct> NA, NA, 10, NA, NA, NA, NA, 1e+05, NA, NA, NA, NA, NA...
## $ stress <fct> always, NA, sometimes, often, NA, NA, sometimes, alwa...
## $ stress12 <fct> NA, NA, no, yes, NA, NA, NA, no, NA, NA, NA, NA, NA, ...
## $ stresses <fct> NA, very likely, NA, somewhat likely, somewhat likely...
## $ strredpg <fct> no, NA, yes, yes, NA, NA, no, yes, NA, no, no, NA, NA...
## $ suicide1 <fct> yes, NA, no, yes, NA, yes, NA, NA, yes, no, yes, no, ...
## $ suicide2 <fct> yes, NA, no, no, NA, no, NA, NA, no, no, no, no, no, ...
## $ suicide3 <fct> yes, NA, no, no, NA, no, NA, NA, no, no, no, no, no, ...
## $ suicide4 <fct> yes, NA, no, no, NA, no, NA, NA, NA, no, no, no, no, ...
## $ supcares <fct> somewhat true, NA, somewhat true, very true, NA, NA, ...
## $ supervis <fct> doesnt supervise, NA, supervises, supervises, NA, NA,...
## $ suphelp <fct> somewhat true, NA, not too true, very true, NA, NA, s...
## $ tax <fct> too high, too high, NA, NA, too high, too high, too h...
## $ teamsafe <fct> strongly agree, NA, agree, strongly agree, NA, NA, ag...
## $ teens <fct> 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
## $ teensex <fct> almst always wrg, NA, always wrong, always wrong, NA,...
## $ tempgen <fct> extremely dangerous, NA, NA, NA, NA, extremely danger...
## $ theism <fct> strongly agree, NA, neither agree nor disagree, NA, N...
## $ thnkself <fct> NA, most important, most important, 2nd important, 3r...
## $ threaten <fct> never, never, NA, NA, less than once a year, never, l...
## $ tlkclrgy <fct> NA, yes, NA, yes, no, NA, yes, no, NA, yes, NA, yes, ...
## $ tlkfam <fct> NA, yes, NA, yes, NA, NA, yes, yes, NA, yes, NA, yes,...
## $ toofast <fct> disagree, NA, disagree, NA, NA, disagree, NA, NA, dis...
## $ toofewwk <fct> often, NA, often, sometimes, NA, NA, never, often, ne...
## $ trbigbus <fct> NA, 7, NA, 6, 8, NA, 6, 2, NA, 7, NA, 3, NA, 5, NA, N...
## $ trcourts <fct> NA, 7, NA, 8, 8, NA, 1, 5, NA, 6, NA, 4, NA, 7, NA, N...
## $ trdunion <fct> NA, NA, disagree, disagree, NA, NA, agree, disagree, ...
## $ trust <fct> NA, can trust, can't be too careful, can trust, can t...
## $ trustman <fct> disagree, NA, agree, agree, NA, NA, agree, agree, agr...
## $ trustsci <fct> strongly agree, NA, strong disagree, NA, NA, not agre...
## $ trynewjb <fct> somewhat likely, NA, not at all likely, not at all li...
## $ tvhours <fct> 3, NA, 1, 1, NA, 10, NA, NA, 4, 2, 3, 3, 8, NA, 8, 5,...
## $ unemp <fct> NA, no, no, no, no, NA, no, no, no, yes, NA, yes, NA,...
## $ unhappy <fct> NA, never, NA, rarely, never, NA, rarely, rarely, NA,...
## $ union <fct> NA, r belongs, neither belongs, spouse belongs, neith...
## $ union1 <fct> NA, r belongs, neither belongs, spouse or partner bel...
## $ unrelat <fct> NA, 0, 0, 0, NA, 0, 0, NA, NA, 0, 1, NA, NA, 0, 0, 0,...
## $ upsdowns <fct> NA, very likely, NA, not very likely, somewhat likely...
## $ upset <fct> NA, never, NA, rarely, never, NA, rarely, sometimes, ...
## $ uscitzn <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, a...
## $ usedup <fct> sometimes, NA, often, sometimes, NA, NA, sometimes, s...
## $ usetech <fct> 100, NA, 100, 70, NA, NA, 0, 75, 33, 2, 30, 0, NA, 10...
## $ usewww <fct> NA, NA, NA, NA, NA, NA, NA, NA, yes, NA, NA, NA, NA, ...
## $ uswary <fct> yes, NA, NA, NA, NA, no, NA, NA, NA, NA, no, NA, yes,...
## $ version <int> 1, 3, 2, 2, 3, 1, 3, 3, 2, 2, 1, 2, 1, 3, 2, 1, 2, 1,...
## $ vetyears <fct> none, none, none, none, more than 4 yrs, none, none, ...
## $ vigfrnd <fct> NA, definitely willing, NA, probably willing, definit...
## $ viggrp <fct> NA, definitely willing, NA, probably willing, probabl...
## $ viglabel <fct> NA, very likely, NA, somewhat likely, NA, NA, very li...
## $ vigmar <fct> NA, definitely willing, NA, probably unwilling, proba...
## $ vignei <fct> NA, probably willing, NA, probably willing, probably ...
## $ vigsoc <fct> NA, probably willing, NA, probably willing, definitel...
## $ vigversn <fct> NA, 6, NA, 44, 85, NA, 37, 54, NA, 46, NA, 71, NA, 25...
## $ vigwork <fct> NA, definitely willing, NA, probably unwilling, proba...
## $ viruses <fct> true, NA, true, NA, NA, false, NA, NA, false, NA, fal...
## $ visitors <fct> no visitors, no visitors, no visitors, no visitors, n...
## $ visnhist <fct> 1, NA, 3, NA, NA, 0, NA, NA, 0, NA, 0, NA, 0, NA, 0, ...
## $ vissci <fct> 0, NA, 3, NA, NA, 1, NA, NA, 0, NA, 0, NA, 0, NA, 0, ...
## $ vistholy <fct> never, NA, never, NA, NA, never, NA, NA, never, NA, n...
## $ viszoo <fct> 2, NA, 2, NA, NA, 1, NA, NA, 0, NA, 1, NA, 0, NA, 0, ...
## $ vote12 <fct> voted, voted, voted, voted, voted, voted, voted, did ...
## $ vote16 <fct> voted, voted, voted, voted, voted, voted, voted, vote...
## $ vpsu <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1,...
## $ vstrat <fct> 3301, 3301, 3301, 3301, 3301, 3301, 3301, 3301, 3301,...
## $ watergen <fct> extremely dangerous, NA, NA, NA, NA, extremely danger...
## $ waypaid <fct> paid by the hour, NA, paid by the hour, salaried, NA,...
## $ wayraise <fct> NA, not very likely, NA, not at all likely, somewhat ...
## $ wealth <fct> NA, NA, "$250,000 to $500,000", "$1 million to $2 mil...
## $ webmob <fct> NA, NA, NA, NA, NA, NA, NA, NA, yes, NA, NA, NA, yes,...
## $ weekswrk <fct> 52, 0, 52, 52, 0, 0, 52, 52, NA, 50, 52, 40, 0, 52, 0...
## $ weight <fct> 235, NA, 225, 170, NA, NA, NA, 135, NA, 193, 175, 212...
## $ where1 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ where11 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ where2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ where3 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, institution, NA, ...
## $ where4 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ where5 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ where6 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ where7 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ whoelse1 <fct> no, no, no, no, no, no, no, no, no, no, no, yes, no, ...
## $ whoelse2 <fct> no, no, no, no, no, no, no, no, yes, no, no, no, no, ...
## $ whoelse3 <fct> no, no, no, yes, no, no, no, no, no, yes, no, no, no,...
## $ whoelse4 <fct> no, no, no, no, no, no, yes, no, no, no, no, no, no, ...
## $ whoelse5 <fct> no, no, no, no, no, no, no, no, no, no, no, no, no, n...
## $ whoelse6 <fct> yes, yes, yes, no, yes, yes, no, yes, no, no, yes, no...
## $ whynopet <fct> NA, too expensive, NA, too much time or work to care ...
## $ whywkhme <fct> worker wants to work at home, NA, worker wants to wor...
## $ widowed <fct> NA, no, no, no, no, NA, no, NA, NA, no, no, no, no, n...
## $ wkageism <fct> no, NA, no, no, NA, NA, no, no, no, no, no, no, NA, n...
## $ wkdecide <fct> sometimes, NA, sometimes, often, NA, NA, often, somet...
## $ wkfreedm <fct> somewhat true, NA, somewhat true, very true, NA, NA, ...
## $ wkharoth <fct> no, NA, no, no, NA, NA, no, no, no, no, no, no, NA, n...
## $ wkharsex <fct> no, NA, no, no, NA, NA, no, no, no, no, no, no, NA, n...
## $ wkpraise <fct> maybe, NA, yes, yes, NA, NA, yes, maybe, NA, maybe, y...
## $ wkracism <fct> no, NA, no, no, NA, NA, no, no, no, no, no, no, NA, n...
## $ wksexism <fct> no, NA, no, yes, NA, NA, no, no, no, no, no, no, NA, ...
## $ wksmooth <fct> agree, NA, agree, strongly agree, NA, NA, agree, stro...
## $ wksub <fct> yes, NA, yes, yes, NA, NA, no, yes, no, yes, no, yes,...
## $ wksub1 <fct> yes, NA, yes, yes, NA, NA, no, yes, no, yes, no, yes,...
## $ wksubs <fct> yes, NA, yes, yes, NA, NA, NA, yes, NA, yes, NA, yes,...
## $ wksubs1 <fct> yes, NA, yes, yes, NA, NA, NA, yes, NA, yes, NA, yes,...
## $ wksup <fct> yes, NA, yes, yes, NA, NA, no, yes, no, no, yes, no, ...
## $ wksup1 <fct> yes, NA, yes, yes, NA, NA, no, yes, no, no, yes, no, ...
## $ wksups <fct> no, NA, no, no, NA, NA, NA, no, NA, NA, yes, NA, NA, ...
## $ wksups1 <fct> no, NA, no, no, NA, NA, NA, no, NA, NA, yes, NA, NA, ...
## $ wkvsfam <fct> rarely, NA, sometimes, rarely, NA, NA, never, sometim...
## $ wlthblks <fct> 4, NA, 4, 5, NA, NA, NA, NA, 6, 5, NA, 5, 3, NA, 5, N...
## $ wlthhsps <fct> 5, NA, 4, NA, NA, NA, NA, NA, 4, NA, NA, NA, 3, NA, 3...
## $ wlthwhts <fct> 4, NA, 4, 4, NA, NA, NA, NA, rich, 4, NA, 3, 4, NA, 5...
## $ worda <fct> correct, NA, correct, correct, NA, correct, NA, NA, c...
## $ wordb <fct> correct, NA, correct, correct, NA, correct, NA, NA, c...
## $ wordc <fct> correct, NA, incorrect, incorrect, NA, incorrect, NA,...
## $ wordd <fct> correct, NA, correct, correct, NA, correct, NA, NA, c...
## $ worde <fct> correct, NA, correct, correct, NA, correct, NA, NA, c...
## $ wordf <fct> correct, NA, correct, correct, NA, correct, NA, NA, c...
## $ wordg <fct> incorrect, NA, incorrect, correct, NA, correct, NA, N...
## $ wordh <fct> correct, NA, incorrect, correct, NA, correct, NA, NA,...
## $ wordi <fct> correct, NA, correct, correct, NA, correct, NA, NA, c...
## $ wordj <fct> correct, NA, incorrect, correct, NA, correct, NA, NA,...
## $ wordsum <fct> 9, NA, 6, 9, NA, 9, NA, NA, 6, 6, 7, 6, 6, NA, 2, 5, ...
## $ workblks <fct> 6, NA, 4, 4, NA, 4, NA, NA, 2, 4, 4, 4, 4, NA, 5, 4, ...
## $ workdiff <fct> strongly agree, NA, agree, strongly agree, NA, NA, ag...
## $ workfast <fct> strongly agree, NA, disagree, strongly agree, NA, NA,...
## $ workfor1 <fct> for-profit company, NA, for-profit company, non-profi...
## $ workhard <fct> NA, 3rd important, 2nd important, most important, mos...
## $ workhsps <fct> 2, NA, 4, 4, NA, 4, NA, NA, 3, 4, 4, 2, 4, NA, 3, 4, ...
## $ workwhts <fct> 4, NA, 4, 4, NA, 4, NA, NA, 3, 4, 4, 3, 5, NA, 5, 3, ...
## $ wrkgovt <fct> private, private, private, private, private, private,...
## $ wrkhome <fct> a few times a year, NA, a few times a year, never, NA...
## $ wrksched <fct> day shift, NA, night shift, day shift, NA, NA, day sh...
## $ wrkslf <fct> someone else, someone else, someone else, someone els...
## $ wrkslffam <fct> NA, NA, NA, NA, NA, NA, NA, NA, no, NA, NA, NA, NA, N...
## $ wrkstat <fct> "temp not working", "retired", "working fulltime", "w...
## $ wrktime <fct> not at all true, NA, not too true, very true, NA, NA,...
## $ wrktype <fct> "regular, permanent employee", NA, "regular, permanen...
## $ wrkwayup <fct> agree strongly, NA, neither agree nor disagree, neith...
## $ wtss <fct> 2.3574927741331, 0.94299710965324, 0.94299710965324, ...
## $ wtssall <fct> 2.3574927741331, 0.94299710965324, 0.94299710965324, ...
## $ wtssnr <fct> 2.75353123823189, 1.10141249529276, 1.10141249529276,...
## $ wwwhr <fct> 20, NA, 10, 6, NA, 3, NA, NA, 8, 1, 10, 3, 2, NA, 5, ...
## $ wwwmin <fct> 0, NA, 0, 0, NA, 0, NA, NA, 0, 30, 0, 0, 0, NA, 0, 0,...
## $ xmarsex <fct> always wrong, always wrong, NA, NA, always wrong, alm...
## $ xmarsex1 <fct> always wrong, NA, always wrong, NA, NA, almost always...
## $ xmovie <fct> NA, no, no, no, no, NA, no, no, no, no, NA, no, NA, n...
## $ xnorcsiz <fct> "uninc,med city", "uninc,med city", "uninc,med city",...
## $ year <int> 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018,...
## $ yearsjob <fct> 1, NA, 15, 25, NA, NA, 2, 5, 0.75, 11, 2, 5, NA, 15, ...
## $ yearsusa <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2...
## $ yearval <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
## $ yousup <fct> 45, NA, 3, 10, NA, NA, NA, 14, NA, NA, 7, NA, NA, 12,...
## $ zodiac <fct> virgo, aquarius, aries, aries, cancer, scorpio, leo, ...head(gss)Observations in dataset: 2348 Variables in dataset: 1065 For fun: total count including NAs: (2438*1065)-(1065+2348)=2,593,057
We are interested in a subset of variables, so we will make a smaller dataframe of the variables of interest using the dplyr package. We will call the new dataframe gss_subset. Please see the metadata and the questionnaire in the lab folder on Sakai for these variables. You can also easily search for the variable by name at this website to get the information. https://gssdataexplorer.norc.org/variables/vfilter?doslider=1&keyword=&page_v=8&search_type=&subjects=&years=&yrmax=2018&yrmin=2018#var_459
natenvir (response variable) nattime
educ sex race income16 pres16 age
extra variables that we won’t use, but you can play around with. natpark natsci natenrgy hunt1 hrs2
gss_select<-gss %>%
select( "natenvir", "nattime", "nataccess", "natpark", "natenrgy", "natsci", "confed", "consci", "hunt1", "hrs2", "age", "sex", "racecen1", "hispanic", "educ", "income16", "pres16")
head(gss_select)Question 3 In the chunk below, use the levels() function to determine the levels of the response variable natenvir. What are the levels of the variable natenvir? What are the levels of the two explanatory variables of interest (nattime, nataccess)? (5 points)
levels(gss_select$natenvir)## [1] "too little" "about right" "too much" "DK" "IAP"
## [6] "NA"Levels of the variable natenvir: “too little”, “about right”, “too much”, “Don’t Know”, “IAP”, “No answer”
levels(gss_select$nattime)## [1] "strongly agree" "somewhat agree" "somewhat disagree"
## [4] "strongly disagree" "Don't know" "IAP"
## [7] "No answer"Levels of the variable nattime: “strongly agree”,“somewhat agree”,“somewhat disagree”, “strongly disagree”, “Don’t know”, “IAP”,No answer"
levels(gss_select$nataccess)## [1] "strongly agree" "somewhat agree" "somewhat disagree"
## [4] "strongly disagree" "Don't know" "IAP"
## [7] "No answer"Levels of the variable nataccess: “strongly agree”, “somewhat agree”,“somewhat disagree”, “strongly disagree”, “Don’t know”,“IAP”,“No answer”
Question 5 Below you will make a basic barplot of the variable natenvir. Properly label and title the plot in the chunk below. Add color to make the plot attractive. Check out STHDA bar plots for more information (http://www.sthda.com/english/wiki/ggplot2-barplots-quick-start-guide-r-software-and-data-visualization). [You can earn five bonus points if you figure out how to developed a stacked bar chart of multiple varibles in the same figure.] (5 points)
ggplot(data=gss_select, aes(x=natenvir, y=nattime, fill=nataccess)) +
geom_bar(stat="identity")+
labs(title="Stacked Bar Chart of Natenvir",
x="natenvir levels", y = "nattime levels")
We are interested in developing a model to explain the variation in beliefs about spending on the environment (the variable natenvir). To make things easier (although I typically wouldn’t recommend this), we will recode the variable into two categories so we can use a logistic model. We will make a binary “too little” and “enough or too much”. To do this, we need to recode the variable. we will use the dplyr function recode. Read more about recode here: https://dplyr.tidyverse.org/reference/recode.html.
Before I recode, I often like to see the counts of each category. https://dplyr.tidyverse.org/reference/count.html.
Using the pipe and the count() function, R calculates how many respondents said that spending on environment is about right, too little or too much.
gss_select %>% count(natenvir)Not answered has 1191 counts which interestingly enough is greater than the other three counts combined. The data is skewed towards the response that there’s not enough money being spent on the environment.
Question 6 In the same way we calculated the counts for natenvir above, in the chunk below, please calculate the counts for the variables nattime and nataccess.Describe the frequencies in a sentence or two. (5 points)
gss_select %>% count(nattime)Not answered holds a large portion of the results with 1201. The data is weighted more towards strongly agree with 408 counts, while somewhat agree is 347, and 251 for somewhat disagree. Strongly disagree only has 141 votes.
gss_select %>% count(nataccess)Similarly to nattime, nataccess has more counts for strongly agree at 885 votes, but tapers off quicker. Somewhat agree has 214 counts, 30 for somewhat disagree and strongly disagree only has 16.
Let’s now calculate the percent of respondents across gender and how they responded to the question about funding to improve the environment (natenvir). We can do this using the table() and prop.table() functions in base R.
The function table() gives us counts of each of the levels across the two variables. The function prop.table() calculates the proportion. I calculated the proportion by column, so i set the argument as 2. Please read more about prop.table() in the help. What happens if you switch the argument in prop.table to 1?
table.gss<-table(gss_select$natenvir, gss_select$sex)
table.gss##
## male female
## too little 285 505
## about right 124 160
## too much 33 50
## DK 0 0
## IAP 0 0
## NA 0 0prop.table.gss<-prop.table(table.gss,2)
prop.table.gss##
## male female
## too little 0.64479638 0.70629371
## about right 0.28054299 0.22377622
## too much 0.07466063 0.06993007
## DK 0.00000000 0.00000000
## IAP 0.00000000 0.00000000
## NA 0.00000000 0.00000000help(prop.table)## starting httpd help server ... doneIf you use 2 in the prop.table function, it makes it a proportion of the levels, and 1 is a proportion for the gender category. In other words, 2 creates a proportion for the columns, 1 creates a proportion for the rows
Question 7 In the chunk below, calculate the proportion of women who spend various amounts of time in nature. Remember the text of the question is: Usually, I spend time in natural environments, such as public parks, gardens or trails, at least once a week.
Discuss the proportions in a sentence. (5 points)
table.gss<-table(gss_select$nattime, gss_select$sex)
table.gss##
## male female
## strongly agree 196 212
## somewhat agree 171 176
## somewhat disagree 128 123
## strongly disagree 60 81
## Don't know 0 0
## IAP 0 0
## No answer 0 0prop.table.gss<-prop.table(table.gss,2)
prop.table.gss##
## male female
## strongly agree 0.3531532 0.3581081
## somewhat agree 0.3081081 0.2972973
## somewhat disagree 0.2306306 0.2077703
## strongly disagree 0.1081081 0.1368243
## Don't know 0.0000000 0.0000000
## IAP 0.0000000 0.0000000
## No answer 0.0000000 0.000000035.8% of females strongly agree that they spend time in natural environments at least once a week, 29.7% of females somewhat agree that they spend time in natural environments at least once a week, 20.7% of females somewhat disagree that they spend time in natural environments at least once a week, and only 13.6% of females strongly disagree that they spend time in natural environments at least once a week.
Now that we know the counts and proportions, let’s recode the variable natenvir into a binary variable so we can use a logistic model. I will call the new variable natenvir.binary. As you see, there are three extraneous levels (DK, IAP, NA). None of the three have any observations.
I will code “too much” as a “1”, “about right” as a “1” and too little as a “0”. We want the variable to be a factor, so we will make it as a factor as well.
gss_select$natenvir.binary<-as.factor(recode(gss_select$natenvir, "too much"= 1,
"about right" = 1,
"too little" = 0))
gss_select %>% count(natenvir.binary)Question 8 Before we make the model, please run counts on each of the additional explanatory variables. Discuss why it may be challenging to include the variables ‘as is’ in the model. Also discuss any shortcomings for how these variables are measured (5 points).
gss_select %>% count(nattime)gss_select %>% count(nataccess)gss_select %>% count(sex)gss_select %>% count(racecen1)gss_select %>% count(hispanic)gss_select %>% count(income16)gss_select %>% count(pres16)gss_select %>% count(educ)gss_select %>% count(age)Besides the names not being the clearest, each data frame has different sizes (e.g 5x2, 5x2, 2x2, 15x2, 20x2 etc) which wouldn’t make a consistent format. The shortcomings for these variables are that the income ranges aren’t consistent.
Now that we have seen the data, we will need to clean it up a bit to get it ready for our model.
We can change the variables age and educ into integers (numeric) to include into our model. For ease of interpretation (not ideal, but fine for our purposes), we will treat responses to nattime (time in nature) and nataccess (access to nature) as continuous numeric data. Run the chunk below and see how R recoded the factor variables to numeric variables.
gss_select$age<-as.numeric(gss_select$age) #makes the variable age numeric
gss_select$educ<-as.numeric(gss_select$educ) #makes education numeric
gss_select$nattime.int<-as.numeric(gss_select$nattime) #makes nattime numeric
gss_select$nataccess.int<-as.numeric(gss_select$nataccess) #makes nataccess numeric
head(gss_select$nattime)## [1] <NA> strongly agree <NA> strongly agree strongly agree
## [6] <NA>
## 7 Levels: strongly agree somewhat agree ... No answerhead(gss_select$nattime.int)## [1] NA 1 NA 1 1 NAhead(gss_select$nataccess)## [1] <NA> strongly agree <NA> strongly agree strongly agree
## [6] <NA>
## 7 Levels: strongly agree somewhat agree ... No answerhead(gss_select$nataccess.int)## [1] NA 1 NA 1 1 NAAs you saw above, income has multiple categories. We probably don’t want to include that many variables in our model. We will recode the income variable into three levels (low, medium, high). It is challenging to determine what should be considered low, medium and high income since incomes vary across regions in the US and a livable income depends on the number of household members, among other factors. For the sake of our model, We will consider high income anything over $110,000. Medium income between $50,000 and $109999 and low income below $50,000. I did the recoding for you. You’re welcome (you owe me a beer =) ).
gss_select$income16.recode<-recode(gss_select$income16, "under $1 000" = "low",
"$1 000 to 2 999" = "low",
"$3 000 to 3 999" = "low",
"$4 000 to 4 999" = "low",
"$5 000 to 5 999" = "low",
"$6 000 to 6 999" = "low",
"$7 000 to 7 999" = "low",
"$8 000 to 9 999" = "low",
"$10000 to 12499" = "low",
"$12500 to 14999" = "low",
"$15000 to 17499" = "low",
"$17500 to 19999" = "low",
"$20000 to 22499" = "low",
"$22500 to 24999" = "low",
"$25000 to 29999" = "low",
"$30000 to 34999" = "low",
"$35000 to 39999" = "low",
"$40000 to 49999" = "low",
"$50000 to 59999" = "medium",
"$60000 to 74999" = "medium",
"$75000 to $89999" = "medium",
"$90000 to $109999" = "medium",
"$110000 to $129999" = "high",
"$130000 to $149999" = "high",
"$150000 to $169999" = "high",
"$170000 or over" = "high"
)
gss_select %>% count(income16.recode)Question 9 Now we will look at the variable racecen1. Please run the chunk below to see the counts of the racecen1 variable. Why is it challenging and not ideal to include the variable ‘as is’ in a model as an explanatory variable? (5 points)
gss_select %>% count(racecen1)The grouping of races are either from a continent or country which is inconsistent. It is ideal to recode to have a concise groups/fewer categories of races.
As you see, many Asian ethnicities are represented in the sample. For the purpose of this model (and I recognize that this isn’t ideal), I will recode the racecen1 variable to group Asian ethnicities together.There are also 28 respondents who listed their race as ‘some other race’. I will combine Guamanian and Other Pacific Islander with this group (again, not ideal).
gss_select$racecen1.recode<-recode(gss_select$racecen1, "asian indian" = "Asian",
"chinese" = "Asian",
"filipino" = "Asian",
"japanese" = "Asian",
"korean" = "Asian",
"vietnamese" = "Asian",
"other asian" = "Asian",
"guamanian or chamorro" = "some other race",
"other pacific islander" = "some other race")
gss_select %>% count(racecen1.recode) And now we will recode the pres16 variable. If respondents reported voting for President Trump in 2016, we will recode the variable a 1, all else a zero. Here I am using the function ifelse(). The new recoding variable is called pres16.recode.
gss_select$pres16.recode<-ifelse(gss_select$pres16 == "trump", 1, 0)
gss_select %>% count(pres16) gss_select %>% count(pres16.recode) Let’s now make our model to predict natenvir.binary. We want to explain the response variable (natenvir.binary) with variables of nattime and nataccess, controlling for age, gender, income, race, Hispanic ethnicity, and political ideology (proxy: if they voted for Trump in 2016). Remember that our response variable is 1= enough or too much spending on improving the environment and zero represents too little spending.
When we include categorical variables in a model, R automatically drops one level–because of the dummy variable trap.
For the variable racecen1.recode, the level not included in the model is ‘white’, so when interpreting the race coefficients, the odds ratios are compared to white.The level that is left out of the income16.recode variable is low–therefore when discussing the odds ratio on income16.recodemedium, the comparison group is low income.
model.1<-glm(data=gss_select, natenvir.binary~nattime.int + nataccess.int + age+racecen1.recode+sex+educ+ pres16.recode + income16.recode, family=binomial)
summary(model.1)##
## Call:
## glm(formula = natenvir.binary ~ nattime.int + nataccess.int +
## age + racecen1.recode + sex + educ + pres16.recode + income16.recode,
## family = binomial, data = gss_select)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.6214 -0.7680 -0.5821 1.0652 2.2483
##
## Coefficients:
## Estimate Std. Error z value
## (Intercept) -0.765556 0.871262 -0.879
## nattime.int 0.135401 0.137376 0.986
## nataccess.int -0.638613 0.328923 -1.942
## age 0.015888 0.007739 2.053
## racecen1.recodeblack or african american 0.422771 0.376376 1.123
## racecen1.recodeamerican indian or alaska native -15.488553 916.921203 -0.017
## racecen1.recodeAsian 0.490853 0.749075 0.655
## racecen1.recodesome other race 1.802438 0.942775 1.912
## racecen1.recodehispanic 0.504420 0.660064 0.764
## sexfemale -0.360550 0.262995 -1.371
## educ -0.027622 0.050077 -0.552
## pres16.recode 1.269930 0.319068 3.980
## income16.recodemedium 0.058042 0.304715 0.190
## income16.recodehigh -0.071334 0.378596 -0.188
## Pr(>|z|)
## (Intercept) 0.3796
## nattime.int 0.3243
## nataccess.int 0.0522 .
## age 0.0401 *
## racecen1.recodeblack or african american 0.2613
## racecen1.recodeamerican indian or alaska native 0.9865
## racecen1.recodeAsian 0.5123
## racecen1.recodesome other race 0.0559 .
## racecen1.recodehispanic 0.4447
## sexfemale 0.1704
## educ 0.5812
## pres16.recode 6.89e-05 ***
## income16.recodemedium 0.8489
## income16.recodehigh 0.8506
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 403.38 on 337 degrees of freedom
## Residual deviance: 362.30 on 324 degrees of freedom
## (2010 observations deleted due to missingness)
## AIC: 390.3
##
## Number of Fisher Scoring iterations: 15Now we can exponentiate the coefficients by using the function exp(coef(model_name)).
exp(coef(model.1)) # to get the odds ratios## (Intercept)
## 4.650754e-01
## nattime.int
## 1.144996e+00
## nataccess.int
## 5.280241e-01
## age
## 1.016015e+00
## racecen1.recodeblack or african american
## 1.526185e+00
## racecen1.recodeamerican indian or alaska native
## 1.876752e-07
## racecen1.recodeAsian
## 1.633709e+00
## racecen1.recodesome other race
## 6.064413e+00
## racecen1.recodehispanic
## 1.656025e+00
## sexfemale
## 6.972929e-01
## educ
## 9.727557e-01
## pres16.recode
## 3.560602e+00
## income16.recodemedium
## 1.059759e+00
## income16.recodehigh
## 9.311511e-01Question 10 Discuss the model results above in terms of the original question about the relationship between time and nature, access to nature and support for funding for the environment. Interpret the odds ratios on age and the two explanatory variables of interest–time in nature (nattime) and access to nature (nataccess). What variables are significant in the model? (10 points) nataccess, age, race, president
The orginial question examines the time spent in nature & acccess to nature (explanatory) with how much we think should be spent (response). The results from the odds ratio shows that the time spent in nature (nattime) are 1.14 times more likely to agree that there is enough money spent on the environment (level: strongly agree). The amount you agree with how much access you have to nature (nataccess) you will be 0.528 more times as likely to agree that there is enough money spent on the environment.
Odds ratio on age, nattime, and access. age: 1.02: As age icreases, you are 1.02 times more likely to believe there is enough money spent on the environment. nattime: 1.14: Spending less time in nature is associated with being 1.14 times more likely to be a 1 for natenvir, which means there is enough money spent on the environment. nattaccess: 0.53: As access to the environment increases, you are 0.53 times more likely to believe there is enough money spent on the environment.