Exploration, Confirmation, and Replication in the Same Observational Study: A Two Team Cross-Screening Approach to Studying the Effect of Unwanted Pregnancy on Mothers' Later Life Outcomes

TL;DR

This paper introduces a novel two team cross-screening method for observational studies, allowing exploratory, confirmatory, and replication analyses within a single dataset to study the effects of unwanted pregnancies on mothers' later life outcomes.

Contribution

The paper proposes a new cross-screening approach enabling comprehensive analysis in one study, addressing multiple testing and hypothesis generation challenges.

Findings

The method successfully identified potential effects of unwanted pregnancies on health and well-being.

Teams' analysis plans were validated through cross-screening, reducing false positives.

The approach facilitates hypothesis generation and testing within a single observational dataset.

Abstract

The long term consequences of unwanted pregnancies carried to term on mothers have not been much explored. We use data from the Wisconsin Longitudinal Study (WLS) and propose a novel approach, namely two team cross-screening, to study the possible effects of unwanted pregnancies carried to term on various aspects of mothers' later-life mental health, physical health, economic well-being and life satisfaction. Our method, unlike existing approaches to observational studies, enables the investigators to perform exploratory data analysis, confirmatory data analysis and replication in the same study. This is a valuable property when there is only a single data set available with unique strengths to perform exploratory, confirmatory and replication analysis. In two team cross-screening, the investigators split themselves into two teams and the data is split as well according to a meaningful covariate. Each team then performs exploratory data analysis on its part of the data to design an analysis plan for the other part of the data. The complete freedom of the teams in designing the analysis has the potential to generate new unanticipated hypotheses in addition to a prefixed set of hypotheses. Moreover, only the hypotheses that looked promising in the data each team explored are forwarded for analysis (thus alleviating the multiple testing problem). These advantages are demonstrated in our study of the effects of unwanted pregnancies on mothers' later life outcomes.