The Cox proportional hazards model has been pervasively used in many social science areas to examine the effects of covariates on timing to an event. The standard Cox model is intended to study univariate survival data where there is a singular event of interest, which can only be experienced once. However, we may additionally wish to explore a…

In social and behavioral sciences, data are typically not normally distributed, which can invalidate hypothesis testing and lead to unreliable results when being analyzed by methods developed for normal data. The existing methods of generating multivariate non-normal data typically create data according to specific univariate marginal measures…

In social and behavioral sciences, data are typically not normally distributed, which can invalidate hypothesis testing and lead to unreliable results when being analyzed by methods developed for normal data. The existing methods of generating multivariate non-normal data typically create data according to specific univariate marginal measures…

A novel approach to integrating Cluster Analysis (CA) within qualitative inquiry is presented, grounded in a large, unstructured dataset from open and rather unstructured interviews. This dataset was previously subjected to typical (theory sensitive) thematic analyses. Transformed into quantitative binary matrix structures, the CA offers…

In the field of social sciences, certain tasks, such as the identification of typologies and the characterization of groups of individuals according to a set of questions, tend to pose a challenge for researchers. Further complications arise if the chosen rating scale is from 0 to 10, since the responses can be treated either as metric or…

A map provides a unique view over the complex relationships of competition and complementarity between methods. It goes beyond the usual approaches to methods, namely monographic, mixed, encyclopaedic and classificatory. A diverse set of 50 social and political science methods instructors were surveyed about their specialty along 17 dimensions…

In its standard formulation, sequence analysis aims at finding typical patterns in a set of life courses represented as sequences. Recently, some proposals have been introduced to jointly analyze sequences defined on different domains (e.g., work career, partnership, and parental histories). We introduce measures to evaluate whether a set of…

It is necessary to test for equivalence of measurements across groups to guarantee that comparisons of regression coefficients or mean scores of a latent factor are meaningful. Unfortunately, when tested, many scales display nonequivalence. Several researchers have suggested that nonequivalence may be used as a useful source of information as to…

In psychology and the behavioral sciences generally, the use of the hierarchical linear model (HLM) and its extensions for discrete outcomes are popular methods for modeling clustered data. HLM and its discrete outcome extensions, however, are certainly not the only methods available to model clustered data. Although other methods exist and are…

Knowledge about different health-related attitudes, beliefs, and risks is of significant interest to scholars in different Social Science disciplines. Usually knowledge is collected in a form of multiple variables and then constructed as a composite indicator. The question any researcher working with knowledge-related variables faces is: what is…

Questionnaires that include items eliciting count responses are becoming increasingly common in psychology. This study proposes methodological techniques to overcome some of the challenges associated with analyzing multivariate item response data that exhibit zero inflation, maximum inflation, and heaping at preferred digits. The modeling…

High dimensional multivariate data, where the number of variables approaches or exceeds the sample size, is an increasingly common occurrence for social scientists. Several tools exist for dealing with such data in the context of univariate regression, including regularization methods such as Lasso, Elastic net, Ridge Regression, as well as the…

Measuring values in sociological research sometimes involves the use of ranking data. A disadvantage of a ranking assignment is that the order in which the items are presented might influence the choice preferences of respondents regardless of the content being measured. The standard procedure to rule out such effects is to randomize the order of…

Objectives: This study examined how evaluation and intervention research (IR) studies assessed statistical change to ascertain effectiveness. Methods: Studies from six core social work journals (2009-2013) were reviewed (N = 1,380). Fifty-two evaluation (n= 27) and intervention (n = 25) studies met the inclusion criteria. These studies were…

Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…