Search results for "Binary response"
showing 3 items of 3 documents
A matrix-valued Bernoulli distribution
2006
AbstractMatrix-valued distributions are used in continuous multivariate analysis to model sample data matrices of continuous measurements; their use seems to be neglected for binary, or more generally categorical, data. In this paper we propose a matrix-valued Bernoulli distribution, based on the log-linear representation introduced by Cox [The analysis of multivariate binary data, Appl. Statist. 21 (1972) 113–120] for the Multivariate Bernoulli distribution with correlated components.
Exploring the Interaction Effects of Gender Contentedness and Pubertal Timing on Adolescent Longitudinal Psychological and Behavioral Health Outcomes
2021
Background: Off-time pubertal timing (PT) and non-conforming gender identity have been reported to predict adverse health and well-being in adolescents. However, the joint effects of these two factors are less addressed. We aimed to investigate the main and interaction effects of gender identity, proxied by perceived gender contentedness (GC), and PT on longitudinal adolescent psychological and behavioral outcomes.Methods: Data (N = 1806, Mage = 13.3 ± 0.5 years) come from the Taiwan Youth Project, which prospectively followed a longitudinal cohort of Taiwanese junior high school students from 2000 (wave 1) to 2009 (wave 9). GC was self-reported at waves 1 and 9 in a binary response, and th…
2013
Currently, a growing number of programs become available in statistical software for multiple imputation of missing values. Among others, two algorithms are mainly implemented: Expectation Maximization (EM) and Multiple Imputation by Chained Equations (MICE). They have been shown to work well in large samples or when only small proportions of missing data are to be imputed. However, some researchers have begun to impute large proportions of missing data or to apply the method to small samples. A simulation was performed using MICE on datasets with 50, 100 or 200 cases and four or eleven variables. A varying proportion of data (3% - 63%) was set as missing completely at random and subsequent…