Problems with zscore standardizing

Hello everyone,

I used the search option and did not find anything similar to my problem. If you do have in mind a discussion about this topic, please refer me to it.

In order to display the results of my findings in a way easy to read, I would like to standardize the variables. It is my understanding that this process does not change the significance level of the variables. Unfortunantly, I was not able to achieve this.

Some details about my data that might be of help to figure out where my mistake is:

I have a panel dataset and I calculate a re-xtlogit model with a binary dependet variable (dep). Further there are two explanatory variables, one is continous between 0 and 1 (cont01) and the other is a dummy variable (dum1). I use both of them with a one period lag, and I use an interaction term between these two. Additionally there are five control variables, two are dummy variables (cd1 cd2), one is categorical (c3) and two can have positive integer values (i.e age) (c4 c5).

Here is what I did:

1. I did my usual regression model: xtlogit dep c.l.cont01##c.l.dum1 cd1 cd2 c3 c4 c5, re

2. I used the zscore command for cont01, c1, c3, c4, c5 without any additional options: zscore cont01, c3, c4, c5

Stata replied:
z_cont01 created with 47 missing values
z_c3 created with 0 missing values
z_c4 created with 0 missing values
z_c5 created with 0 missing values

These are the same numbers of missing values present in the data before.

3. I did the same regession as in (1) but with the variables obtained from zscore: xtlogit dep c.l.z_cont01##c.l.dum1 cd1 cd2 z_c3 z_c4 z_c5, re

I get the same results in terms of significance for all the variables except the l.dum1. The p-value was 0,076 before and is now 0,818. Again, the significance for the interaction term and the l.cont01 remain the same.

Where is my mistake? How can I get standarized results?

Thanks to everbody for taking your time. Every thought or comment is appreciated.

Best,
Keith