[R] Different LLRs on multinomial logit models in R and SPSS
Sören Vogel
sovo0815 at gmail.com
Thu Jan 6 17:06:44 CET 2011
Hello, after calculating a multinomial logit regression on my data, I
compared the output to an output retrieved with SPSS 18 (Mac). The
coefficients appear to be the same, but the logLik (and therefore fit)
values differ widely. Why?
The regression in R:
set.seed(1234)
df <- data.frame(
"y"=factor(sample(LETTERS[1:3], 143, repl=T, prob=c(4, 1, 10))),
"a"=sample(1:5, 143, repl=T),
"b"=sample(1:7, 143, repl=T),
"c"=sample(1:2, 143, repl=T)
)
library(nnet)
mod1 <- multinom(y ~ ., data=df, trace=F)
deviance(mod1) # 199.0659
mod0 <- update(mod1, . ~ 1, trace=FALSE)
deviance(mod0) # 204.2904
Output data and syntax for SPSS:
df2 <- df
df2[, 1] <- as.numeric(df[, 1])
write.csv(df2, file="dfxy.csv", row.names=F, na="")
syntaxfile <- "dfxy.sps"
cat('GET DATA
/TYPE=TXT
/FILE=\'', getwd(), '/dfxy.csv\'
/DELCASE=LINE
/DELIMITERS=","
/QUALIFIER=\'"\'
/ARRANGEMENT=DELIMITED
/FIRSTCASE=2
/IMPORTCASE=ALL
/VARIABLES=
y "F1.0"
a "F8.4"
b "F8.4"
c "F8.4".
CACHE.
EXECUTE.
DATASET NAME DataSet1 WINDOW=FRONT.
VALUE LABELS
/y 1 "A" 2 "B" 3 "C".
EXECUTE.
NOMREG y (BASE=1 ORDER=ASCENDING) WITH a b c
/CRITERIA CIN(95) DELTA(0) MXITER(100) MXSTEP(5) CHKSEP(20)
LCONVERGE(0) PCONVERGE(0.000001)
SINGULAR(0.00000001)
/MODEL
/STEPWISE=PIN(.05) POUT(0.1) MINEFFECT(0) RULE(SINGLE)
ENTRYMETHOD(LR) REMOVALMETHOD(LR)
/INTERCEPT=INCLUDE
/PRINT=FIT PARAMETER SUMMARY LRT CPS STEP MFI IC.
', file=syntaxfile, sep="", append=F)
-> Loglik0: 135.02
-> Loglik1: 129.80
Thanks, Sören
More information about the R-help
mailing list