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Probit analysis is applied in a situation where analysis of covariance (ANCOVA) would customarily be used. The dichotomous dependent variables arise from dichotomizations of skewed continuous variables recorded as the proportion of time certain activities are observed. The probit approach avoids the biases of ordinary A NCO VA that arise due to skewness (limited variation). To illustrate this, data from 225 experiments and 214 control subjects in a drug treatment program was analyzed. It was found that the probit approach was able to reveal more substantial treatment effects than the ordinary A NCO VA.

AbstractThis article discusses new latent variable techniques developed by the authors. As an illustration, a new factor mixture model is applied to the monozygotic–dizygotic twin analysis of binary items measuring alcohol-use disorder. In this model, heritability is simultaneously studied with respect to latent class membership and within-class severity dimensions. Different latent classes of individuals are allowed to have different heritability for the severity dimensions. The factor mixture approach appears to have great potential for the genetic analyses of heterogeneous populations. Generalizations for longitudinal data are also outlined.

"The purpose of this book is to provide researchers with information that is not readily available to them and that we believe is important for their research. Many topics such as linear regression analysis; mediation analysis; causal inference; regression analysis with categorical, count, and censored outcomes; Bayesian analysis; and missing data analysis have entire books devoted to them. This book does not attempt to replace these books but rather to give useful and manageable summaries of these topics and show how the analyses are implemented in Mplus. The technical level is kept at a minimum but still requires an introductory statistics background and a good background in regression"

AbstractIn previous studies we obtained evidence that variation in loneliness has a genetic component. Based on adult twin data, the heritability estimate for loneliness, which was assessed as an ordinal trait, was 48%. These analyses were done on loneliness scores averaged over items ('I feel lonely' and 'Nobody loves me') and over time points. In this article we present a longitudinal analysis of loneliness data assessed in 5 surveys (1991 through 2002) in Dutch twins (N = 8389) for the two separate items of the loneliness scale. From the longitudinal growth modeling it was found sufficient to have non-zero variance for the intercept only, while the other effects (linear, quadratic and cubic slope) had zero variance. For the item 'I feel lonely' we observed an increasing age trend up to age 30, followed by a decline to age 50. Heritability for individual differences in the intercept was estimated at 77%. For the item 'Nobody loves me' no significant trend over age was seen; the heritability of the intercept was estimated at 70%.