Homework from 3.2.15 - Try2
Selecting a Data Set
1. Selecting a dataset
I will be using the 2014 General Social Survey dataset which records hundreds of questions about the polled population from the year 2014. These questions can be used together to show different relationships between different variables, that might be relevant for 2014. For example, examining questions about abortion compared to a person’s age and gender, may be helpful in seeing the difference between generational and gender gaps on public opinion about abortions.
2. Data I will be using
As previously mentioned, I would be interested in looking at data that examine the relatively current population’s answers to questions about abortion compared with age, marital status, sex, and education level. The following will be the variables I will be using:
AGE Respondent’s Age SEX Respondent’s Sex MARITAL Marital Status EDUC Highest year of school completed ABDEFECT Abortion if there is a strong chance of a serious defect for the baby ABNOMORE Abortion if the woman is married but wants no more children ABHLTH Abortion if the woman’s health is seriously endangered ABPOOR Abortion if the family cannot afford more children ABRAPE Abortion if the woman became pregnant as a result of rape? ABSINGLE Abortion if the woman does not want to marry the father of the child ABANY Abortion if the woman wants one for any reason
3. Theories that may connect these variables
We can speculate that if we examine the relationships of these variables, females may be more likely to be pro-abortion in all cases, while males may be less likely in all cases. Also, we speculate that the younger a respondent, the more open they may be to supporting abortion for different scenarios. Education level may also show a positive relationship between supporting abortion and amount of schooling completed.
4. Creation of dataset
The dataset I have created is labeled “Abortion” There are still some errors I am processing, see below.
library(Zelig)
library(foreign)
library(DescTools)
d <- read.dta("/Users/laurenberkowitz/Downloads/GSS2014.DTA", convert.factors = FALSE)
names(d)library(dplyr)
Abortion <- select(d, age, sex, marital, educ, abdefect, abnomore, abhlth, abpoor, abrape, absingle, abany)
names(Abortion)5. Regression Analysis
For a regression analysis to begin, I will compare the sex and age of the respondents with their answers to questions of agreement with abortion generally (abany).
demog1 <- lm(abany ~ age, data=Abortion)The first regression analysis is showing the relationship of age to people’s support for abortion when pregnancy is as a result of rape.
demog2 <- lm(abany ~ sex, data=Abortion)The second regression analysis is showing the relationship of age and gender to people’s support for abortion when pregnancy is as a result of rape.
demog3 <- lm(abany ~ educ, data=Abortion)The third regression analysis is showing the relationship of age, sex and education level to people’s support for abortion when pregnancy is as a result.
library(stargazer)##
## Please cite as:
##
## Hlavac, Marek (2014). stargazer: LaTeX code and ASCII text for well-formatted regression and summary statistics tables.
## R package version 5.1. http://CRAN.R-project.org/package=stargazerstargazer(demog1, demog2, demog3, type="text")##
## ==========================================================================================
## Dependent variable:
## ----------------------------------------------------------------------
## abany
## (1) (2) (3)
## ------------------------------------------------------------------------------------------
## age 0.002***
## (0.001)
##
## sex 0.023
## (0.025)
##
## educ -0.042***
## (0.004)
##
## Constant 1.460*** 1.513*** 2.124***
## (0.036) (0.040) (0.053)
##
## ------------------------------------------------------------------------------------------
## Observations 1,646 1,653 1,652
## R2 0.004 0.001 0.070
## Adjusted R2 0.003 -0.0001 0.069
## Residual Std. Error 0.497 (df = 1644) 0.498 (df = 1651) 0.480 (df = 1650)
## F Statistic 6.705*** (df = 1; 1644) 0.858 (df = 1; 1651) 124.001*** (df = 1; 1650)
## ==========================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01plot(demog1)
plot(demog2)
plot(demog3)
We see here that there is a small positive relationship (0.002) between age and the likelihood that someone will support abortion and are significant with a 99% confidence rate. Surprisingly it appears that the relationship between sex of the person surveyed does not significantly impact their likelihood to be in support of abortion when pregnancy is as a result of rape. There seems to be a small but significant negative relationship (-0.042) between the education level of the person surveyed and their likelihood to be in support of abortion when pregnancy is as a result of rape. This means that the higher a person’s education, the less likely they are to be in support of abortion when a pregnancy is as a result of rape.
6. Discussion
We see from the results that there is some room for explanation. The age and education variables alone already present significant results just from independent relationships between the variables and support for an abortion if the pregnancy is as a result of rape. Further exploration of combined variables which may increase the effect and also exploration of these variables on questions of abortion in relation to other pregnancy scenarios can be examined in the future.