Replicating the Results of Martin Elff’s Analysis of American National Election Study of 1948 (without using the memisc package)
Xiomara Vilchez
Sunday, March 29, 2015
Introduction
For this analysis we will be replicating the results that Martin Elff published about his analysis of the American National Election Study of 1948. The Anes contains data from the USA wide surveys that were conducted between October and November of 1948 during the election between Truman and Dewey. This data set collected includes a total of 662 cases with 65 variables.
Analysis
In order to analyze and replicate what Elff did in his study we had to download the ANES dataset. Since variables were not easily understood we recoded them, we use the variables V480018 which we recoded to “vote” in order to signify respondents that voted and did not vote. We used the variable V480029 and renamed it “occupation.hh” which signifies the respondents education. The variable V480045 turned into “gender” to signify respondents sex. The variable V480047 changed to age to signify respondents age and so on. The steps to recode and rename these variables are depicted below.
options(digits=3)
nes1948.por <- UnZip("anes/NES1948.ZIP","NES1948.POR", package="memisc")
nes1948 <- spss.portable.file(nes1948.por)nes1948<-read.spss(nes1948.por)names(nes1948)## [1] "VVERSION" "VDSETNO" "V480001" "V480002" "V480003" "V480004"
## [7] "V480005" "V480006" "V480007" "V480008" "V480009" "V480010"
## [13] "V480011" "V480012" "V480013" "V480014A" "V480014B" "V480015A"
## [19] "V480015B" "V480016A" "V480016B" "V480017A" "V480017B" "V480018"
## [25] "V480019" "V480020" "V480021A" "V480021B" "V480022A" "V480022B"
## [31] "V480023" "V480024" "V480025A" "V480025B" "V480026" "V480027"
## [37] "V480028" "V480029" "V480030" "V480031A" "V480031B" "V480031C"
## [43] "V480032A" "V480032B" "V480032C" "V480033A" "V480033B" "V480034A"
## [49] "V480034B" "V480035A" "V480035B" "V480036A" "V480036B" "V480037"
## [55] "V480038" "V480039" "V480040" "V480041" "V480042" "V480043"
## [61] "V480044" "V480045" "V480046" "V480047" "V480048" "V480049"
## [67] "V480050"description(nes1948)vote.48<- select(vote.48,
V480018,
V480029,
V480030,
V480045,
V480046,
V480047,
V480048,
V480049,
V480050)
str(vote.48)## 'data.frame': 662 obs. of 9 variables:
## $ V480018: Factor w/ 7 levels "VOTED - FOR TRUMAN",..: 1 2 1 2 1 2 2 1 2 1 ...
## $ V480029: Factor w/ 12 levels "PROFESSIONAL, SEMI-PROFESSIONAL",..: 6 3 4 1 1 2 7 7 4 4 ...
## $ V480030: Factor w/ 4 levels "YES","NO","DK",..: 1 2 2 2 2 2 2 2 1 1 ...
## $ V480045: Factor w/ 3 levels "MALE","FEMALE",..: 1 2 2 2 1 2 1 2 1 1 ...
## $ V480046: Factor w/ 4 levels "WHITE","NEGRO",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ V480047: Factor w/ 7 levels "18-24","25-34",..: 3 3 2 3 2 3 4 5 2 2 ...
## $ V480048: Factor w/ 4 levels "GRADE SCHOOL",..: 1 2 2 3 3 2 1 1 2 2 ...
## $ V480049: Factor w/ 8 levels "UNDER $500","$500-$999",..: 4 7 5 7 5 7 5 2 5 6 ...
## $ V480050: Factor w/ 6 levels "PROTESTANT","CATHOLIC",..: 1 1 2 1 2 1 1 1 1 2 ...vote.48<-rename(vote.48, V480018="vote", V480029="Occupation.hh", V490030= "unionized.hh", V480045="gender", V480046="race", V480047="age", V480048="education", V480049="total.income", V480050="religious.pref")Graphic Description
The following is a graphical representation of the variables included in the subset vote.48. We are given frequency and percent of the 9 variables that are included in this data frame.
Desc(vote.48, plotit=TRUE)##
## -------------------------------------------------------------------------
## 'data.frame': 662 obs. of 9 variables:
## 1 $ vote : Factor w/ 7 levels "VOTED - FOR TRUMAN",..: 1 2 1 2 1 2 2 1 2 1 ...
## 2 $ Occupation.hh : Factor w/ 12 levels "PROFESSIONAL, SEMI-PROFESSIONAL",..: 6 3 4 1 1 2 7 7 4 4 ...
## 3 $ V480030 : Factor w/ 4 levels "YES","NO","DK",..: 1 2 2 2 2 2 2 2 1 1 ...
## 4 $ gender : Factor w/ 3 levels "MALE","FEMALE",..: 1 2 2 2 1 2 1 2 1 1 ...
## 5 $ race : Factor w/ 4 levels "WHITE","NEGRO",..: 1 1 1 1 1 1 1 1 1 1 ...
## 6 $ age : Factor w/ 7 levels "18-24","25-34",..: 3 3 2 3 2 3 4 5 2 2 ...
## 7 $ education : Factor w/ 4 levels "GRADE SCHOOL",..: 1 2 2 3 3 2 1 1 2 2 ...
## 8 $ total.income : Factor w/ 8 levels "UNDER $500","$500-$999",..: 4 7 5 7 5 7 5 2 5 6 ...
## 9 $ religious.pref: Factor w/ 6 levels "PROTESTANT","CATHOLIC",..: 1 1 2 1 2 1 1 1 1 2 ...
##
## -------------------------------------------------------------------------
## 1 - vote (factor)
##
## length n NAs levels unique dupes
## 662 662 0 7 7 y
##
## level freq perc cumfreq cumperc
## 1 DID NOT VOTE 238 .360 238 .360
## 2 VOTED - FOR TRUMAN 212 .320 450 .680
## 3 VOTED - FOR DEWEY 178 .269 628 .949
## 4 VOTED - NA FOR WHOM 20 .030 648 .979
## 5 VOTED - FOR OTHER 11 .017 659 .995
## 6 NA WHETHER VOTED 2 .003 661 .998
## 7 VOTED - FOR WALLACE 1 .002 662 1.000
## -------------------------------------------------------------------------
## 2 - Occupation.hh (factor)
##
## length n NAs levels unique dupes
## 662 662 0 12 12 y
##
## level freq perc cumfreq cumperc
## 1 SKILLED AND SEMI-SKILLED 164 .248 164 .248
## 2 FARM OPERATORS AND MANAGERS 105 .159 269 .406
## 3 UNSKILLED, INCLUDING FARM AND SERVICE W 85 .128 354 .535
## 4 OTHER WHITE-COLLAR (CLERICAL, SALES, ET 79 .119 433 .654
## 5 SELF-EMPLOYED, MANAGERIAL, SUPERVISORY 73 .110 506 .764
## 6 PROFESSIONAL, SEMI-PROFESSIONAL 44 .066 550 .831
## 7 RETIRED, TOO OLD OR UNABLE TO WORK 38 .057 588 .888
## 8 HOUSEWIFE 28 .042 616 .931
## 9 NA 28 .042 644 .973
## 10 STUDENT 7 .011 651 .983
## 11 PROTECTIVE SERVICE 6 .009 657 .992
## 12 UNEMPLOYED 5 .008 662 1.000
## -------------------------------------------------------------------------
## 3 - V480030 (factor)
##
## length n NAs levels unique dupes
## 662 662 0 4 4 y
##
## level freq perc cumfreq cumperc
## 1 NO 493 .745 493 .745
## 2 YES 150 .227 643 .971
## 3 NA 14 .021 657 .992
## 4 DK 5 .008 662 1.000
## -------------------------------------------------------------------------
## 4 - gender (factor)
##
## length n NAs levels unique dupes
## 662 662 0 3 3 y
##
## level freq perc cumfreq cumperc
## 1 FEMALE 357 .539 357 .539
## 2 MALE 302 .456 659 .995
## 3 NA 3 .005 662 1.000
## -------------------------------------------------------------------------
## 5 - race (factor)
##
## length n NAs levels unique dupes
## 662 662 0 4 3 y
##
## level freq perc cumfreq cumperc
## 1 WHITE 585 .884 585 .884
## 2 NEGRO 60 .091 645 .974
## 3 NA 17 .026 662 1.000
## 4 OTHER 0 .000 662 1.000
## -------------------------------------------------------------------------
## 6 - age (factor)
##
## length n NAs levels unique dupes
## 662 662 0 7 7 y
##
## level freq perc cumfreq cumperc
## 1 35-44 174 .263 174 .263
## 2 25-34 142 .215 316 .477
## 3 45-54 125 .189 441 .666
## 4 55-64 86 .130 527 .796
## 5 65 AND OVER 70 .106 597 .902
## 6 18-24 57 .086 654 .988
## 7 NA 8 .012 662 1.000
## -------------------------------------------------------------------------
## 7 - education (factor)
##
## length n NAs levels unique dupes
## 662 662 0 4 4 y
##
## level freq perc cumfreq cumperc
## 1 GRADE SCHOOL 292 .441 292 .441
## 2 HIGH SCHOOL 266 .402 558 .843
## 3 COLLEGE 100 .151 658 .994
## 4 NA 4 .006 662 1.000
## -------------------------------------------------------------------------
## 8 - total.income (factor)
##
## length n NAs levels unique dupes
## 662 662 0 8 8 y
##
## level freq perc cumfreq cumperc
## 1 $2000-2999 185 .279 185 .279
## 2 $3000-3999 142 .215 327 .494
## 3 $1000-1999 110 .166 437 .660
## 4 $5000 AND OVER 84 .127 521 .787
## 5 $4000-4999 66 .100 587 .887
## 6 $500-$999 43 .065 630 .952
## 7 UNDER $500 25 .038 655 .989
## 8 NA 7 .011 662 1.000
## -------------------------------------------------------------------------
## 9 - religious.pref (factor)
##
## length n NAs levels unique dupes
## 662 662 0 6 6 y
##
## level freq perc cumfreq cumperc
## 1 PROTESTANT 460 .695 460 .695
## 2 CATHOLIC 140 .211 600 .906
## 3 JEWISH 25 .038 625 .944
## 4 NONE 18 .027 643 .971
## 5 OTHER 14 .021 657 .992
## 6 NA 5 .008 662 1.000
Further Analysis
In his study Elff wanted to further recode a few of the variables that he chose from the subset vote.48 in order to make them simpler as shown below.
vote.48$vote3<- recode(vote.48$vote, "'VOTED - FOR TRUMAN' = 'TRUMAN'")
vote.48$vote3<-recode(vote.48$vote, "'VOTED - FOR DEWEY' = 'DEWEY'")
vote.48$vote3<-recode(vote.48$vote, "'VOTED - FOR WALLACE' = 'OTHER'")
vote.48$vote3<- recode(vote.48$vote, "'VOTED - FOR OTHER' = 'OTHER'")vote.48$occup4<-recode(vote.48$Occupation.hh, "'PROFESSIONAL, SEMI-PROFESSIONAL' = 'Upper White Collar'")
vote.48$occup4<-recode(vote.48$Occupation.hh, "'SELF-EMPLOYED, MANAGERIAL, SUPERVISORY' = 'Upper White Collar'")
vote.48$occup4<-recode(vote.48$Occupation.hh, "'OTHER WHITE-COLLAR (CLERICAL, SALES, ET' = 'Other White Collar'" )
vote.48$occup4<-recode(vote.48$Occupation.hh, "'SKILLED AND SEMI-SKILLED' = 'Blue Collar'")
vote.48$occup4<-recode(vote.48$Occupation.hh, "'PROTECTIVE SERVICE' = 'Blue Collar'")
vote.48$occup4<-recode(vote.48$Occupation.hh, "'UNSKILLED, INCLUDING FARM AND SERVICE W' = 'Blue Collar'")
vote.48$occup4<-recode(vote.48$Occupation.hh, "'FARM OPERATORS AND MANAGERS' = 'Farmer'")vote.48$relig3<-recode(vote.48$religious.pref, "'PROTESTANT' = 'Protestant'")
vote.48$relig3<-recode(vote.48$religious.pref, "'CATHOLIC' = 'Catholic'")
vote.48$relig3<-recode(vote.48$religious.pref, "'JEWISH' = 'Other,none'")
vote.48$relig3<-recode(vote.48$religious.pref, "'OTHER' = 'Other,none'")
vote.48$relig3<-recode(vote.48$religious.pref, "'NONE' = 'Other,none'")vote.48$race2<-recode(vote.48$race, "'WHITE' = 'White'")
vote.48$race2<-recode(vote.48$race, "'NEGRO' = 'Black'")Cross Tabulations
crsst<-CrossTable(votenew$vote3, votenew$relig3)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 105
##
##
## | votenew$relig3
## votenew$vote3 | CATHOLIC | NA | PROTESTANT | Row Total |
## --------------------|------------|------------|------------|------------|
## DID NOT VOTE | 6 | 3 | 51 | 60 |
## | 0.107 | 0.964 | 0.004 | |
## | 0.100 | 0.050 | 0.850 | 0.571 |
## | 0.500 | 1.000 | 0.567 | |
## | 0.057 | 0.029 | 0.486 | |
## --------------------|------------|------------|------------|------------|
## OTHER | 0 | 0 | 3 | 3 |
## | 0.343 | 0.086 | 0.071 | |
## | 0.000 | 0.000 | 1.000 | 0.029 |
## | 0.000 | 0.000 | 0.033 | |
## | 0.000 | 0.000 | 0.029 | |
## --------------------|------------|------------|------------|------------|
## VOTED - FOR DEWEY | 1 | 0 | 13 | 14 |
## | 0.225 | 0.400 | 0.083 | |
## | 0.071 | 0.000 | 0.929 | 0.133 |
## | 0.083 | 0.000 | 0.144 | |
## | 0.010 | 0.000 | 0.124 | |
## --------------------|------------|------------|------------|------------|
## VOTED - FOR TRUMAN | 4 | 0 | 22 | 26 |
## | 0.356 | 0.743 | 0.004 | |
## | 0.154 | 0.000 | 0.846 | 0.248 |
## | 0.333 | 0.000 | 0.244 | |
## | 0.038 | 0.000 | 0.210 | |
## --------------------|------------|------------|------------|------------|
## VOTED - NA FOR WHOM | 1 | 0 | 1 | 2 |
## | 2.604 | 0.057 | 0.298 | |
## | 0.500 | 0.000 | 0.500 | 0.019 |
## | 0.083 | 0.000 | 0.011 | |
## | 0.010 | 0.000 | 0.010 | |
## --------------------|------------|------------|------------|------------|
## Column Total | 12 | 3 | 90 | 105 |
## | 0.114 | 0.029 | 0.857 | |
## --------------------|------------|------------|------------|------------|
##
## crsst<-CrossTable(votenew$vote3, votenew$race2)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 105
##
##
## | votenew$race2
## votenew$vote3 | Black | NA | WHITE | Row Total |
## --------------------|-----------|-----------|-----------|-----------|
## DID NOT VOTE | 12 | 4 | 44 | 60 |
## | 3.857 | 1.286 | 0.925 | |
## | 0.200 | 0.067 | 0.733 | 0.571 |
## | 1.000 | 1.000 | 0.494 | |
## | 0.114 | 0.038 | 0.419 | |
## --------------------|-----------|-----------|-----------|-----------|
## OTHER | 0 | 0 | 3 | 3 |
## | 0.343 | 0.114 | 0.082 | |
## | 0.000 | 0.000 | 1.000 | 0.029 |
## | 0.000 | 0.000 | 0.034 | |
## | 0.000 | 0.000 | 0.029 | |
## --------------------|-----------|-----------|-----------|-----------|
## VOTED - FOR DEWEY | 0 | 0 | 14 | 14 |
## | 1.600 | 0.533 | 0.384 | |
## | 0.000 | 0.000 | 1.000 | 0.133 |
## | 0.000 | 0.000 | 0.157 | |
## | 0.000 | 0.000 | 0.133 | |
## --------------------|-----------|-----------|-----------|-----------|
## VOTED - FOR TRUMAN | 0 | 0 | 26 | 26 |
## | 2.971 | 0.990 | 0.712 | |
## | 0.000 | 0.000 | 1.000 | 0.248 |
## | 0.000 | 0.000 | 0.292 | |
## | 0.000 | 0.000 | 0.248 | |
## --------------------|-----------|-----------|-----------|-----------|
## VOTED - NA FOR WHOM | 0 | 0 | 2 | 2 |
## | 0.229 | 0.076 | 0.055 | |
## | 0.000 | 0.000 | 1.000 | 0.019 |
## | 0.000 | 0.000 | 0.022 | |
## | 0.000 | 0.000 | 0.019 | |
## --------------------|-----------|-----------|-----------|-----------|
## Column Total | 12 | 4 | 89 | 105 |
## | 0.114 | 0.038 | 0.848 | |
## --------------------|-----------|-----------|-----------|-----------|
##
## crsst<-CrossTable(votenew$vote3, votenew$occup4)##
##
## Cell Contents
## |-------------------------|
## | N |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 105
##
##
## | votenew$occup4
## votenew$vote3 | Farmer | Row Total |
## --------------------|-----------|-----------|
## DID NOT VOTE | 60 | 60 |
## | 0.571 | |
## --------------------|-----------|-----------|
## OTHER | 3 | 3 |
## | 0.029 | |
## --------------------|-----------|-----------|
## VOTED - FOR DEWEY | 14 | 14 |
## | 0.133 | |
## --------------------|-----------|-----------|
## VOTED - FOR TRUMAN | 26 | 26 |
## | 0.248 | |
## --------------------|-----------|-----------|
## VOTED - NA FOR WHOM | 2 | 2 |
## | 0.019 | |
## --------------------|-----------|-----------|
## Column Total | 105 | 105 |
## --------------------|-----------|-----------|
##
## crsst<-CrossTable(votenew$vote3, votenew$gender)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 105
##
##
## | votenew$gender
## votenew$vote3 | MALE | FEMALE | Row Total |
## --------------------|-----------|-----------|-----------|
## DID NOT VOTE | 19 | 41 | 60 |
## | 1.501 | 1.083 | |
## | 0.317 | 0.683 | 0.571 |
## | 0.432 | 0.672 | |
## | 0.181 | 0.390 | |
## --------------------|-----------|-----------|-----------|
## OTHER | 2 | 1 | 3 |
## | 0.439 | 0.317 | |
## | 0.667 | 0.333 | 0.029 |
## | 0.045 | 0.016 | |
## | 0.019 | 0.010 | |
## --------------------|-----------|-----------|-----------|
## VOTED - FOR DEWEY | 9 | 5 | 14 |
## | 1.673 | 1.207 | |
## | 0.643 | 0.357 | 0.133 |
## | 0.205 | 0.082 | |
## | 0.086 | 0.048 | |
## --------------------|-----------|-----------|-----------|
## VOTED - FOR TRUMAN | 13 | 13 | 26 |
## | 0.407 | 0.293 | |
## | 0.500 | 0.500 | 0.248 |
## | 0.295 | 0.213 | |
## | 0.124 | 0.124 | |
## --------------------|-----------|-----------|-----------|
## VOTED - NA FOR WHOM | 1 | 1 | 2 |
## | 0.031 | 0.023 | |
## | 0.500 | 0.500 | 0.019 |
## | 0.023 | 0.016 | |
## | 0.010 | 0.010 | |
## --------------------|-----------|-----------|-----------|
## Column Total | 44 | 61 | 105 |
## | 0.419 | 0.581 | |
## --------------------|-----------|-----------|-----------|
##
## crsst<-CrossTable(votenew$vote3, votenew$education)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 105
##
##
## | votenew$education
## votenew$vote3 | GRADE SCHOOL | HIGH SCHOOL | COLLEGE | NA | Row Total |
## --------------------|--------------|--------------|--------------|--------------|--------------|
## DID NOT VOTE | 39 | 18 | 2 | 1 | 60 |
## | 0.001 | 0.005 | 0.257 | 0.321 | |
## | 0.650 | 0.300 | 0.033 | 0.017 | 0.571 |
## | 0.574 | 0.581 | 0.400 | 1.000 | |
## | 0.371 | 0.171 | 0.019 | 0.010 | |
## --------------------|--------------|--------------|--------------|--------------|--------------|
## OTHER | 3 | 0 | 0 | 0 | 3 |
## | 0.575 | 0.886 | 0.143 | 0.029 | |
## | 1.000 | 0.000 | 0.000 | 0.000 | 0.029 |
## | 0.044 | 0.000 | 0.000 | 0.000 | |
## | 0.029 | 0.000 | 0.000 | 0.000 | |
## --------------------|--------------|--------------|--------------|--------------|--------------|
## VOTED - FOR DEWEY | 8 | 4 | 2 | 0 | 14 |
## | 0.125 | 0.004 | 2.667 | 0.133 | |
## | 0.571 | 0.286 | 0.143 | 0.000 | 0.133 |
## | 0.118 | 0.129 | 0.400 | 0.000 | |
## | 0.076 | 0.038 | 0.019 | 0.000 | |
## --------------------|--------------|--------------|--------------|--------------|--------------|
## VOTED - FOR TRUMAN | 17 | 8 | 1 | 0 | 26 |
## | 0.002 | 0.014 | 0.046 | 0.248 | |
## | 0.654 | 0.308 | 0.038 | 0.000 | 0.248 |
## | 0.250 | 0.258 | 0.200 | 0.000 | |
## | 0.162 | 0.076 | 0.010 | 0.000 | |
## --------------------|--------------|--------------|--------------|--------------|--------------|
## VOTED - NA FOR WHOM | 1 | 1 | 0 | 0 | 2 |
## | 0.067 | 0.284 | 0.095 | 0.019 | |
## | 0.500 | 0.500 | 0.000 | 0.000 | 0.019 |
## | 0.015 | 0.032 | 0.000 | 0.000 | |
## | 0.010 | 0.010 | 0.000 | 0.000 | |
## --------------------|--------------|--------------|--------------|--------------|--------------|
## Column Total | 68 | 31 | 5 | 1 | 105 |
## | 0.648 | 0.295 | 0.048 | 0.010 | |
## --------------------|--------------|--------------|--------------|--------------|--------------|
##
## crsst<-CrossTable(votenew$vote3, votenew$age)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 105
##
##
## | votenew$age
## votenew$vote3 | 18-24 | 25-34 | 35-44 | 45-54 | 55-64 | 65 AND OVER | NA | Row Total |
## --------------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|
## DID NOT VOTE | 8 | 12 | 20 | 4 | 9 | 6 | 1 | 60 |
## | 0.468 | 0.286 | 0.069 | 1.582 | 0.053 | 0.107 | 0.321 | |
## | 0.133 | 0.200 | 0.333 | 0.067 | 0.150 | 0.100 | 0.017 | 0.571 |
## | 0.727 | 0.667 | 0.606 | 0.308 | 0.529 | 0.500 | 1.000 | |
## | 0.076 | 0.114 | 0.190 | 0.038 | 0.086 | 0.057 | 0.010 | |
## --------------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|
## OTHER | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 3 |
## | 0.314 | 0.514 | 0.003 | 1.064 | 0.486 | 1.260 | 0.029 | |
## | 0.000 | 0.000 | 0.333 | 0.333 | 0.000 | 0.333 | 0.000 | 0.029 |
## | 0.000 | 0.000 | 0.030 | 0.077 | 0.000 | 0.083 | 0.000 | |
## | 0.000 | 0.000 | 0.010 | 0.010 | 0.000 | 0.010 | 0.000 | |
## --------------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|
## VOTED - FOR DEWEY | 0 | 2 | 4 | 3 | 3 | 2 | 0 | 14 |
## | 1.467 | 0.067 | 0.036 | 0.926 | 0.237 | 0.100 | 0.133 | |
## | 0.000 | 0.143 | 0.286 | 0.214 | 0.214 | 0.143 | 0.000 | 0.133 |
## | 0.000 | 0.111 | 0.121 | 0.231 | 0.176 | 0.167 | 0.000 | |
## | 0.000 | 0.019 | 0.038 | 0.029 | 0.029 | 0.019 | 0.000 | |
## --------------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|
## VOTED - FOR TRUMAN | 2 | 3 | 8 | 5 | 5 | 3 | 0 | 26 |
## | 0.192 | 0.476 | 0.004 | 0.985 | 0.148 | 0.000 | 0.248 | |
## | 0.077 | 0.115 | 0.308 | 0.192 | 0.192 | 0.115 | 0.000 | 0.248 |
## | 0.182 | 0.167 | 0.242 | 0.385 | 0.294 | 0.250 | 0.000 | |
## | 0.019 | 0.029 | 0.076 | 0.048 | 0.048 | 0.029 | 0.000 | |
## --------------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|
## VOTED - NA FOR WHOM | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
## | 2.982 | 1.260 | 0.629 | 0.248 | 0.324 | 0.229 | 0.019 | |
## | 0.500 | 0.500 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.019 |
## | 0.091 | 0.056 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
## | 0.010 | 0.010 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
## --------------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|
## Column Total | 11 | 18 | 33 | 13 | 17 | 12 | 1 | 105 |
## | 0.105 | 0.171 | 0.314 | 0.124 | 0.162 | 0.114 | 0.010 | |
## --------------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|-------------|
##
## Linear Models
votenew_mod<-glm(vote3~occup4+race2, family = binomial,data=vote.48)
summary(votenew_mod)##
## Call:
## glm(formula = vote3 ~ occup4 + race2, family = binomial, data = vote.48)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.890 -1.106 0.721 0.805 1.794
##
## Coefficients:
## Estimate Std. Error z value
## (Intercept) -1.169 0.337 -3.47
## occup4HOUSEWIFE 0.174 0.433 0.40
## occup4NA 0.873 0.447 1.95
## occup4OTHER WHITE-COLLAR (CLERICAL, SALES, ET 1.772 0.357 4.96
## occup4PROFESSIONAL, SEMI-PROFESSIONAL 1.404 0.412 3.41
## occup4PROTECTIVE SERVICE 1.047 0.905 1.16
## occup4RETIRED, TOO OLD OR UNABLE TO WORK 1.384 0.432 3.20
## occup4SELF-EMPLOYED, MANAGERIAL, SUPERVISORY 1.302 0.335 3.89
## occup4SKILLED AND SEMI-SKILLED 1.131 0.264 4.29
## occup4STUDENT 0.147 0.808 0.18
## occup4UNEMPLOYED -1.216 1.136 -1.07
## occup4UNSKILLED, INCLUDING FARM AND SERVICE W 0.373 0.301 1.24
## race2NA 0.588 0.595 0.99
## race2WHITE 0.998 0.297 3.36
## Pr(>|z|)
## (Intercept) 0.00052 ***
## occup4HOUSEWIFE 0.68790
## occup4NA 0.05068 .
## occup4OTHER WHITE-COLLAR (CLERICAL, SALES, ET 6.9e-07 ***
## occup4PROFESSIONAL, SEMI-PROFESSIONAL 0.00066 ***
## occup4PROTECTIVE SERVICE 0.24719
## occup4RETIRED, TOO OLD OR UNABLE TO WORK 0.00135 **
## occup4SELF-EMPLOYED, MANAGERIAL, SUPERVISORY 0.00010 ***
## occup4SKILLED AND SEMI-SKILLED 1.8e-05 ***
## occup4STUDENT 0.85574
## occup4UNEMPLOYED 0.28449
## occup4UNSKILLED, INCLUDING FARM AND SERVICE W 0.21510
## race2NA 0.32355
## race2WHITE 0.00079 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 864.76 on 661 degrees of freedom
## Residual deviance: 791.15 on 648 degrees of freedom
## AIC: 819.1
##
## Number of Fisher Scoring iterations: 4votenew2_mod<-glm(vote3~education+gender, family = binomial, data=vote.48)
summary(votenew2_mod)##
## Call:
## glm(formula = vote3 ~ education + gender, family = binomial,
## data = vote.48)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.840 -1.205 0.806 0.949 1.150
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.457 0.153 2.98 0.00286 **
## educationHIGH SCHOOL 0.499 0.177 2.82 0.00480 **
## educationCOLLEGE 1.032 0.274 3.76 0.00017 ***
## educationNA 0.641 1.165 0.55 0.58191
## genderFEMALE -0.393 0.169 -2.33 0.02000 *
## genderNA -0.088 1.240 -0.07 0.94342
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 864.76 on 661 degrees of freedom
## Residual deviance: 838.92 on 656 degrees of freedom
## AIC: 850.9
##
## Number of Fisher Scoring iterations: 4Linear Regression
lmod1<-zelig(vote3~occup4+race2, model="logit", data=vote.48)
lmod2<-zelig(vote3~occup4+race2+education, model="logit", data=vote.48)
lmod3<-zelig(vote3~occup4+race2+education+gender, model="logit", data=vote.48)stargazer(lmod1,lmod2,lmod3, type="text")##
## ===========================================================================
## Dependent variable:
## -----------------------------
## vote3
## (1) (2) (3)
## ---------------------------------------------------------------------------
## occup4HOUSEWIFE 0.174 0.141 0.283
## (0.433) (0.434) (0.441)
##
## occup4NA 0.873* 0.820* 0.868*
## (0.447) (0.450) (0.462)
##
## occup4OTHER WHITE-COLLAR (CLERICAL, SALES, ET 1.770*** 1.630*** 1.620***
## (0.357) (0.368) (0.369)
##
## occup4PROFESSIONAL, SEMI-PROFESSIONAL 1.400*** 1.020** 1.040**
## (0.412) (0.448) (0.450)
##
## occup4PROTECTIVE SERVICE 1.050 0.895 0.910
## (0.905) (0.917) (0.910)
##
## occup4RETIRED, TOO OLD OR UNABLE TO WORK 1.380*** 1.410*** 1.380***
## (0.432) (0.434) (0.435)
##
## occup4SELF-EMPLOYED, MANAGERIAL, SUPERVISORY 1.300*** 1.140*** 1.110***
## (0.335) (0.348) (0.350)
##
## occup4SKILLED AND SEMI-SKILLED 1.130*** 1.110*** 1.080***
## (0.264) (0.266) (0.267)
##
## occup4STUDENT 0.147 -0.330 -0.398
## (0.808) (0.863) (0.867)
##
## occup4UNEMPLOYED -1.220 -1.160 -1.230
## (1.140) (1.140) (1.140)
##
## occup4UNSKILLED, INCLUDING FARM AND SERVICE W 0.373 0.360 0.342
## (0.301) (0.302) (0.303)
##
## race2NA 0.588 0.483 0.480
## (0.595) (0.597) (0.604)
##
## race2WHITE 0.998*** 0.917*** 0.909***
## (0.297) (0.301) (0.302)
##
## educationHIGH SCHOOL 0.148 0.163
## (0.197) (0.198)
##
## educationCOLLEGE 0.703** 0.650**
## (0.325) (0.328)
##
## educationNA 0.739 0.559
## (1.240) (1.240)
##
## genderFEMALE -0.336*
## (0.182)
##
## genderNA -0.142
## (1.280)
##
## Constant -1.170*** -1.180*** -0.977***
## (0.337) (0.339) (0.355)
##
## ---------------------------------------------------------------------------
## Observations 662 662 662
## Log Likelihood -396.000 -393.000 -391.000
## Akaike Inf. Crit. 819.000 820.000 821.000
## ===========================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01Analysis
The linear regression shown above are showing the relationship between several demographic characteristics of respondents and whether and whom they voted for in the 1948 election between Truman and Dewey. The first linear regression which I named lmod1 shows the relationship between respondent occupation and race with whom they voted for. The second linear regression adds on respondent education. Finally the third adds the respondents gender. We will be using the first linear model since its margin of error (AIC) is the lowest between all three models.