The impact of IOM recommendations on gestational weight gain among US women: An analysis of birth records during 2011-2019.

The prevailing guidelines of the Institute of Medicine (IOM) of United States on gestational weight gain (GWG) are based on women's prepregnancy body mass index (BMI) categories. Previous research has shown that the guidelines issued in 1990 and revised in 2009 had no effect. We investigate the effectiveness of new guidelines issued in 2009 analyzing the records of all singleton births in the U.

Adversity in Infancy and Childhood Cognitive Development: Evidence From Four Developing Countries.

We investigated whether adverse experiences at age 1 (AE-1) affect the level of and change in cognition during childhood using harmonized data from four developing countries. Data included children born in 2001/2002 and were followed longitudinally in 2006/2007 and in 2009/2010 by Young Lives study in Ethiopia, India, Peru, and Vietnam. Childhood cognition was measured using the Peabody Picture Vocabulary Test (PPVT) at ages 5 (PPVT-5) and 8 (PPVT-8).

Effects of Purchase Restrictions on Smoking During Pregnancy: An Analysis of U.S. Birth Records.

Introduction: In December 2019, the minimum legal sales age (MLSA) for tobacco products in the United States was raised from 18 to 21 years as a measure of preventing smoking initiation. Smoking during pregnancy, which causes maternal, fetal, and infant morbidity and mortality, is a major public health concern. We first study the effects of purchase restrictions on smoking during different stages of pregnancy covering the entire United States and using the records of all live births during 2014-2018 by birthing people aged 18-21 years.

SYSTEMATICALLY MISCLASSIFIED BINARY DEPENDENT VARIABLES.

When a binary dependent variable is misclassified, that is, recorded in the category other than where it really belongs, probit and logit estimates are biased and inconsistent. In some cases the probability of misclassification may vary systematically with covariates, and thus be endogenous. In this paper we develop an estimation approach that corrects for endogenous misclassification, validate our approach using a simulation study, and apply it to the analysis of a treatment program designed to improve family dynamics.

The Pot Calling the Kettle Black? A Comparison of Measures of Current Tobacco Use.

Researchers often use the discrepancy between self-reported and biochemically assessed active smoking status to argue that self-reported smoking status is not reliable, ignoring the limitations of biochemically assessed measures and treating it as the gold standard in their comparisons. Here, we employ econometric techniques to compare the accuracy of self-reported and biochemically assessed current tobacco use, taking into account measurement errors with both methods. Our approach allows estimating and comparing the sensitivity and specificity of each measure without directly observing true smoking status.

Inferring outcrossing in the homothallic fungus Sclerotinia sclerotiorum using linkage disequilibrium decay.

The occurrence and frequency of outcrossing in homothallic fungal species in nature is an unresolved question. Here we report detection of frequent outcrossing in the homothallic fungus Sclerotinia sclerotiorum. In using multilocus linkage disequilibrium (LD) to infer recombination among microsatellite alleles, high mutation rates confound the estimates of recombination.

'Behold, a virgin is with HIV!' misreporting sexual behavior among infected adolescents.

In four Southern African countries where the HIV prevalence rate is among the highest in the world, 46.4% of a sample of female adolescents infected with HIV report having never engaged in sex. This would indicate either the dominance of non-sexual modes of HIV transmission or rampant misreporting of sexual behavior in the sample.

Selection effects and prevention program outcomes.

A primary goal of the paper is to provide an example of an evaluation design and analytic method that can be used to strengthen causal inference in nonexperimental prevention research. We used this method in a nonexperimental multisite study to evaluate short-term outcomes of a preventive intervention, and we accounted for effects of two types of selection bias: self-selection into the program and differential dropout. To provide context for our analytic approach, we present an overview of the counterfactual model (also known as Rubin's causal model or the potential outcomes model) and several methods derived from that model, including propensity score matching, the Heckman two-step approach, and full information maximum likelihood based on a bivariate probit model and its trivariate generalization.

Measuring bias in self-reported data.

Response bias shows up in many fields of behavioural and healthcare research where self-reported data are used. We demonstrate how to use stochastic frontier estimation (SFE) to identify response bias and its covariates. In our application to a family intervention, we examine the effects of participant demographics on response bias before and after participation; gender and race/ethnicity are related to magnitude of bias and to changes in bias across time, and bias is lower at post-test than at pre-test.