P-values become insignificant when st errors are clustered

Dear StataList Members,

Here is my data and I am running cox proportional hazard model using the code. When I do not cluster st errors, the p-values corresponding to the following variables are significant: ideal_distance ideal_larger_zero d_dist_exceed. However, when I cluster them, they lose their significance. Why is that the case? Thank you in advance.

stcox i.male ideal_distance ideal_larger_zero d_dist_exceed mother_age mother_age_sqr i.survey_year i.SEDUC i.rural_urban i.wealth_index i.quarter_of_birth if B0_01==0, robust cluster(CASEID) nohr

Code:

* Example generated by -dataex-. To install: ssc install dataex
clear
input float(male ideal_distance ideal_larger_zero d_dist_exceed mother_age mother_age_sqr survey_year) double SEDUC float(rural_urban wealth_index quarter_of_birth) double B0_01 byte(_st _d) double _t byte _t0 str15 CASEID float age_months_new
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0   .5 0 "       10110  2"   .5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0  1.5 0 "       10110  2"  1.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0  2.5 0 "       10110  2"  2.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0  3.5 0 "       10110  2"  3.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0  4.5 0 "       10110  2"  4.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0  5.5 0 "       10110  2"  5.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0  6.5 0 "       10110  2"  6.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0  7.5 0 "       10110  2"  7.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0  8.5 0 "       10110  2"  8.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0  9.5 0 "       10110  2"  9.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 10.5 0 "       10110  2" 10.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 11.5 0 "       10110  2" 11.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 12.5 0 "       10110  2" 12.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 13.5 0 "       10110  2" 13.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 14.5 0 "       10110  2" 14.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 15.5 0 "       10110  2" 15.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 16.5 0 "       10110  2" 16.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 17.5 0 "       10110  2" 17.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 18.5 0 "       10110  2" 18.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 19.5 0 "       10110  2" 19.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 0 20.5 0 "       10110  2" 20.5
1  0 1 0 36 1296 2008 3 1 5 1 0 1 1 21.5 0 "       10110  2" 21.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0   .5 0 "       102 3  2"   .5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0  1.5 0 "       102 3  2"  1.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0  2.5 0 "       102 3  2"  2.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0  3.5 0 "       102 3  2"  3.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0  4.5 0 "       102 3  2"  4.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0  5.5 0 "       102 3  2"  5.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0  6.5 0 "       102 3  2"  6.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0  7.5 0 "       102 3  2"  7.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0  8.5 0 "       102 3  2"  8.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0  9.5 0 "       102 3  2"  9.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0 10.5 0 "       102 3  2" 10.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0 11.5 0 "       102 3  2" 11.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0 12.5 0 "       102 3  2" 12.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0 13.5 0 "       102 3  2" 13.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0 14.5 0 "       102 3  2" 14.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0 15.5 0 "       102 3  2" 15.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0 16.5 0 "       102 3  2" 16.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 0 17.5 0 "       102 3  2" 17.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 18.5 0 "       102 3  2" 18.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 19.5 0 "       102 3  2" 19.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 20.5 0 "       102 3  2" 20.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 21.5 0 "       102 3  2" 21.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 22.5 0 "       102 3  2" 22.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 23.5 0 "       102 3  2" 23.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 24.5 0 "       102 3  2" 24.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 25.5 0 "       102 3  2" 25.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 26.5 0 "       102 3  2" 26.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 27.5 0 "       102 3  2" 27.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 28.5 0 "       102 3  2" 28.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 29.5 0 "       102 3  2" 29.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 30.5 0 "       102 3  2" 30.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 31.5 0 "       102 3  2" 31.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 32.5 0 "       102 3  2" 32.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 33.5 0 "       102 3  2" 33.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 34.5 0 "       102 3  2" 34.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 35.5 0 "       102 3  2" 35.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 36.5 0 "       102 3  2" 36.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 37.5 0 "       102 3  2" 37.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 38.5 0 "       102 3  2" 38.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 39.5 0 "       102 3  2" 39.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 40.5 0 "       102 3  2" 40.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 41.5 0 "       102 3  2" 41.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 42.5 0 "       102 3  2" 42.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 43.5 0 "       102 3  2" 43.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 44.5 0 "       102 3  2" 44.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 45.5 0 "       102 3  2" 45.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 46.5 0 "       102 3  2" 46.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 47.5 0 "       102 3  2" 47.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 48.5 0 "       102 3  2" 48.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 49.5 0 "       102 3  2" 49.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 50.5 0 "       102 3  2" 50.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 51.5 0 "       102 3  2" 51.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 52.5 0 "       102 3  2" 52.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 53.5 0 "       102 3  2" 53.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 54.5 0 "       102 3  2" 54.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 55.5 0 "       102 3  2" 55.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 56.5 0 "       102 3  2" 56.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 57.5 0 "       102 3  2" 57.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 58.5 0 "       102 3  2" 58.5
1  0 1 0 32 1024 2008 1 1 2 4 0 1 1 59.5 0 "       102 3  2" 59.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0   .5 0 "       10217  1"   .5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0  1.5 0 "       10217  1"  1.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0  2.5 0 "       10217  1"  2.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0  3.5 0 "       10217  1"  3.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0  4.5 0 "       10217  1"  4.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0  5.5 0 "       10217  1"  5.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0  6.5 0 "       10217  1"  6.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0  7.5 0 "       10217  1"  7.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0  8.5 0 "       10217  1"  8.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0  9.5 0 "       10217  1"  9.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0 10.5 0 "       10217  1" 10.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0 11.5 0 "       10217  1" 11.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0 12.5 0 "       10217  1" 12.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0 13.5 0 "       10217  1" 13.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0 14.5 0 "       10217  1" 14.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0 15.5 0 "       10217  1" 15.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0 16.5 0 "       10217  1" 16.5
0 -1 0 0 37 1369 2008 3 1 4 2 0 1 0 17.5 0 "       10217  1" 17.5
end
label values male male
label def male 0 "Female", modify
label def male 1 "Male", modify
label values SEDUC SEDUC
label def SEDUC 1 "Complete primary", modify
label def SEDUC 3 "Complete high school / higher", modify
label values rural_urban rural_urban
label def rural_urban 1 "Urban", modify
label values wealth_index wealth_index
label def wealth_index 2 "Poorer", modify
label def wealth_index 4 "Rich", modify
label def wealth_index 5 "Richest", modify
label values B0_01 B0_01
label def B0_01 0 "Single birth", modify

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P-values become insignificant when st errors are clustered