I created a logistic regression model for the data set immediately below and
obtained the following parameter estimates:
Coefficients :
Estimate Std. Error t-value Pr(>|t|)
altc -0.064539 0.359398 -0.1796 0.8575
alts -0.287682 0.381881 -0.7533 0.4513
Then I reformatted the data so as not to repeat identical observations. The
reformatted data set is near the bottom of this message. I cannot figure
out how to run the logistic regression with the reformatted data. I have
tried using a weight statement, but that has not solved the problem.
Can anyone offer a suggestion? Thanks for any help.
Mark Miller
Gainesville, Florida
# school program style count
new.data <- matrix(c(
1, 1, "s" , 1,
1, 1, "s" , 1,
1, 1, "t" , 1,
1, 1, "t" , 1,
1, 1, "t" , 1,
1, 1, "t" , 1,
1, 1, "c", 1,
1, 1, "c", 1,
1, 2, "s" , 1,
1, 2, "s" , 1,
1, 2, "s" , 1,
1, 2, "s" , 1,
1, 2, "t" , 1,
1, 2, "t" , 1,
1, 2, "t" , 1,
1, 2, "t" , 1,
1, 2, "t" , 1,
1, 2, "t" , 1,
1, 2, "c", 1,
1, 2, "c", 1,
1, 2, "c", 1,
1, 2, "c", 1,
1, 2, "c", 1,
1, 2, "c", 1,
2, 1, "s" , 1,
2, 1, "s" , 1,
2, 1, "t" , 1,
2, 1, "t" , 1,
2, 1, "c", 1,
2, 1, "c", 1,
2, 1, "c", 1,
2, 2, "s" , 1,
2, 2, "s" , 1,
2, 2, "s" , 1,
2, 2, "s" , 1,
2, 2, "t" , 1,
2, 2, "t" , 1,
2, 2, "t" , 1,
2, 2, "t" , 1,
2, 2, "c", 1,
2, 2, "c", 1,
2, 2, "c", 1,
2, 2, "c", 1
), nrow = 43, byrow = TRUE)
new.data2 <- data.frame(new.data)
names(new.data2) <- c("school", "program",
"style", "count")
new.data2$style <- as.factor(new.data2$style)
levels(new.data2$style)
library(mlogit)
mldata <- mlogit.data(new.data2, varying=NULL, choice="style",
shape="wide")
mlogit.model <- mlogit(style ~ 1 , data = mldata, reflevel = "t") ;
summary(mlogit.model)
# school program style count
new.data <- matrix(c(
1, 1, "s" , 2,
1, 1, "t" , 4,
1, 1, "c", 2,
1, 2, "s" , 4,
1, 2, "t" , 6,
1, 2, "c", 6,
2, 1, "s" , 2,
2, 1, "t" , 2,
2, 1, "c", 3,
2, 2, "s" , 4,
2, 2, "t" , 4,
2, 2, "c", 4
), nrow = 12, byrow = TRUE)
new.data2 <- data.frame(new.data)
names(new.data2) <- c("school", "program",
"style", "count")
new.data2$style <- as.factor(new.data2$style)
levels(new.data2$style)
library(mlogit)
mldata <- mlogit.data(new.data2, varying=NULL, choice="style",
shape="wide")
mlogit.model <- mlogit(style ~ 1 , data = mldata, reflevel = "t") ;
summary(mlogit.model)
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