Casual Contraception in Casual Sex
Condom1_Men

Specification
Model Name:Condom1_Men
Title:Men
Description:P(Condom | grade) Among Men
Method:logit
Sample:Condom
Dependent Variable:condom
Independent Variables:sophomore + junior + senior
Subset:if female == 0 & condom >= 0
Time & Date Computed:09:09:15, 9 Jul 2014

Sections in which this model is embedded

  1. CompressedTables — Compressed Tables
  2. MainAnalysis — Tables

Estimates Replay

logit condom sophomore junior senior  if female == 0 & condom >= 0 , 

----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Model Condom1_Men
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Logistic regression                               Number of obs   =       1252
                                                  LR chi2(3)      =       9.20
                                                  Prob > chi2     =     0.0268
Log likelihood = -712.32517                       Pseudo R2       =     0.0064

------------------------------------------------------------------------------
      condom |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   sophomore |  -.4181478   .1808894    -2.31   0.021    -.7726846    -.063611
      junior |  -.4638318   .1898376    -2.44   0.015    -.8359066    -.091757
      senior |  -.4735096   .1854022    -2.55   0.011    -.8368913    -.110128
       _cons |   1.382717   .1336785    10.34   0.000     1.120711    1.644722
------------------------------------------------------------------------------
Scalars
r2_p .0064129920248879
N_cds 0
N_cdf 0
p .0268045905184924
chi2 9.195240335407561
df_m 3
ll_0 -716.9227951416625
k_eq_model 1
ll -712.3251749739587
k_autoCns 0
rc 0
converged 1
k_dv 1
k_eq 1
k 4
ic 3
N 1252
rank 4
Macros
_estimates_name Condom1_Men
cmd logit
cmdline logit condom sophomore junior senior if female == 0 & condom >= 0 ,
estat_cmd logit_estat
predict logit_p
marginsnotok stdp DBeta DEviance DX2 DDeviance Hat Number Residuals RStandard SCore
title Logistic regression
chi2type LR
opt moptimize
vce oim
user mopt__logit_d2()
crittype log likelihood
ml_method d2
singularHmethod m-marquardt
technique nr
which max
depvar condom
properties b V

Matrices

e(b), transpose
y1
condom sophomore -.418147793
condom junior -.463831758
condom senior -.473509648
condom _cons 1.38271652
e(V)
condom condom condom condom
sophomore junior senior _cons
condom sophomore .032720992 .017869944 .017869944 -.017869944
condom junior .017869944 .036038304 .017869944 -.017869944
condom senior .017869944 .017869944 .034373986 -.017869944
condom _cons -.017869944 -.017869944 -.017869944 .017869944
e(mns), transpose
r1
sophomore .269169329
junior .215654952
senior .236421725
_cons 1
e(rules), transpose
r1
c1 0
c2 0
c3 0
c4 0
e(ilog), transpose
r1
c1 -716.922795
c2 -712.347693
c3 -712.325176
c4 -712.325175
c5 0
c6 0
c7 0
c8 0
c9 0
c10 0
c11 0
c12 0
c13 0
c14 0
c15 0
c16 0
c17 0
c18 0
c19 0
c20 0
e(gradient), transpose
r1
condom sophomore 5.7832e-12
condom junior 1.3249e-10
condom senior 2.5111e-10
condom _cons 8.4029e-07