Blundering Ecologist Blundering Ecologist - 15 days ago 9
R Question

Number of dimensions for p-value using stargazer

Another user asked How do I add confidence intervals to odds ratios in stargazer table? and outlined their solution to the problem (I've included the relevant lines of code here)

OR.vector <- exp(mylogit$coef)
CI.vector <- exp(confint(mylogit))
p.values <- summary(mylogit)$coefficients[, 4]

# Table with ORs and CIs`
stargazer(mylogit, coef = list(OR.vector), ci = T,
ci.custom = list(CI.vector), p = list(p.values),
single.row = T, type = "text")

When I try to run the same code for my own model, I receive the following error

Error in summary(ml.TatC)$coefficients[, 4] :
incorrect number of dimensions

Might anyone know why this is happening? Thank you in advance for your help!

UPDATE: Here is a link to the .txt file used.

The code I have used is as follows:

tattoo <- read.table("",
header=TRUE, na.strings=c("unk", "NA"))


Tat<, varying=NULL, shape="wide", choice="size", id.var="date")

ml.Tat<-mlogit(size~1|age+sex+yy, Tat, reflevel="small", id.var="date")


p.values<-summary(ml.Tat)$coefficients[,4] #incorrect # of dimensions, how am I supposed to determine dimensions?

stargazer(ml.Tat, coef=list(OR.vector), ci=TRUE, ci.custom=list(CI.vector), single.row=T, type="text", star.cutoffs=c(0.05,0.01,0.001), out="table1.txt", digits=4)


The mlogit package stores p-values through the function summary.mlogit in $CoefTable, not in $coefficients, as with summary.glm. You can see this:

> str(summary(ml.Tat)$coefficients)
atomic [1:8] -4.45e+02 -1.88e+02 2.51e-02 8.04e-03 1.38 ...

summary(ml.Tat)$coefficients is an atomic vector, so has only one dimension. That's why you are getting the error.

Use summary(ml.Tat)$CoefTable[,4] to extract the p-values you want:

> summary(ml.Tat)$CoefTable[,4]
  large:(intercept) medium:(intercept)   large:age         medium:age          large:sexM        medium:sexM 
  0.000000e+00       0.000000e+00       8.536121e-10       1.731441e-03       0.000000e+00       0.000000e+00 
  large:yy          medium:yy 
  0.000000e+00       0.000000e+00 

So your code should read:



stargazer(ml.Tat, coef=list(OR.vector), ci=TRUE, ci.custom=list(CI.vector),
          p = p.values, single.row=T, type="text",
          out="table1.txt", digits=4)

Your table:

                        Dependent variable:     
large:(intercept)   0.0000*** (0.0000, 0.0000)  
medium:(intercept)    0.0000 (0.0000, 0.0000)   
large:age             1.0254 (1.0172, 1.0336)   
medium:age            1.0081 (1.0030, 1.0132)   
large:sexM            3.9821 (3.5355, 4.4851)   
medium:sexM           2.0886 (1.9576, 2.2284)   
large:yy              1.2455 (1.2189, 1.2726)   
medium:yy             1.0976 (1.0849, 1.1105)   
Observations                  18,162            
R2                            0.0410            
Log Likelihood             -15,882.7000         
LR Test               1,357.1140*** (df = 8)    
Note:              *p<0.05; **p<0.01; ***p<0.001

Good to know (if you are new to R) that packages deploy the summary function differently, so always good to explore the object to see what is going on.