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. Author manuscript; available in PMC: 2018 Aug 4.
Published in final edited form as: Am Sociol Rev. 2017 Aug 4;82(5):945–976. doi: 10.1177/0003122417720466

Table A7.

Multivariate Models Predicting Poor Academic Performance

Doubly-Robust Propensity Score Models
Predicting End of Term Examination
Scores (Percent)a
Female Male
English
Coeff./(se)
(1)
Math
Coeff./(se)
(1)
English
Coeff./(se)
(3)
Math
Coeff./(se)
(3)
Average predicted value if no respondents were in a sexual relationship at wave 3 53.67 48.31 54.89 53.74
Average predicted value if all respondents were in a sexual relationship at wave 3 51.55 47.06 51.90 55.04
Difference in predicted values (estimate of effect size of sexual relationship status on tests scores) −2.11 (2.68) −1.25 (2.83) −2.99 (2.90) 1.30 (3.11)

N 347 347 214 214

Fixed-Effects Logistic Regression Models Predicting Trouble in school during four months preceding interviewb Female OR/(se) (3) Male OR/(se) (4)

Respondent was in a sexual relationship 0.87 (0.25) 1.16 (0.32)
Socio-economic Status 0.99 (0.08) 1.33 (0.16)*
Current Year in School 1.39 (0.16)** 1.39 (0.18)*
Trouble paying school fees over past 4 months 1.11 (0.17) 1.23 (0.21)
Decline in health over past 4 months 1.07 (0.43) 1.37 (0.22)
Probabilistic estimate of being in school in 1 year 0.99 (0.03) 1.03 (0.05)
Employed 2.77 (2.70) 0.30 (0.37)

N: Observations (Respondents) 899 (208) 635 (145)

Notes:

0.10,

*

0.05,

**

0.01,

***

0.001.

a

The doubly robust models account for the following covariates: age, socioeconomic status, current level of school, and attitudes and expectations related to education. I measured all these covariates at wave three and used them to estimate both the propensity scores and the outcome model. The outcome measure was measured at wave 4.

b

All independent variables are lagged by one survey wave, so that variables measured at each point in time predict having trouble in school over the subsequent four months.