Next: Example 5: 2000 pid,
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Previous: Example 3: 1996 pid,
year 2000
VARS
CF0301
CF0704
CF0704A
CF0724
VCF0803
CF9088
CF9096
;
# get rid of unwanted value in party ID
pid <- CF0301;
pid <- ifelse(pid == 9, NA, pid);
# get rid of unwanted value in libcon self-placement
libcon <- VCF0803;
libcon <- ifelse(libcon == 9, NA, libcon);
# presvote3 is three major party candidates only
presvote3 <- CF0704;
# presvote is Dem and Rep candidates only
presvote <- CF0704A - 1;
# watchtv is how much watched campaign on TV
watchtv <- CF0724;
# compute spatial model measure of difference between Dem and Rep candidates
demlibcon <- CF9088;
replibcon <- CF9096;
demdist <- abs(libcon-demlibcon);
repdist <- abs(libcon-replibcon);
distdiff <- demdist-repdist;
# crosstab of libcon given pid
xtable libcon pid
# crosstab of libcon given pid and watchtv
xtable libcon pid watchtv
# crosstab of three-party vote given pid and watchtv
xtable presvote3 pid
# crosstab of two-party vote given pid and watchtv
xtable presvote pid
# one-way frequency table of libcon placements
xtable libcon
xtable demlibcon
xtable replibcon
# simple ordinary least squares regression model of two-party vote
# explanatory variables are PID dummy variables and spatial model difference
summary(lm(presvote ~ factor(pid) + distdiff, weights=wgtXXX));
# simple probit regression model of two-party vote
# explanatory variables are PID dummy variables and spatial model difference
summary(glm(presvote ~ factor(pid) + distdiff,
family=binomial(link="probit"), weights=wgtXXX));
Walter Mebane
2004-11-18