Discrete-time survival analysis (DTSA) models are a popular way of modeling events in the social sciences. However, the analysis of discrete-time survival data is challenged by missing data in one or more covariates. Negative consequences of missing covariate data include efficiency losses and possible bias. A popular approach to circumventing…

The estimation of RxC ecological inference contingency tables from aggregate data is one of the most salient and challenging problems in the field of quantitative social sciences, with major solutions proposed from both the ecological regression and the mathematical programming frameworks. In recent decades, there has been a drive to find…

One of the most important developments in the current era of social sciences is the growing availability and diversity of data, big and small. Social scientists increasingly combine information from multiple data sets in their research. While conducting statistical analyses with linked data is relatively straightforward, borrowing information…

Ensuring a credible literature base is essential for all research fields. One element of this relates to the replicability of published work, which is the probability that the results of an original study would replicate in an independent investigation. A critical feature of replicable research is that the sample size of a study is sufficient to…

In this article, the author will discuss processes used by quantitative researchers to render judgments and decisions about the results of their statistical analyses, highlighting what "'p'-values" represent and how "p"-values became ubiquitous in quantitative social science research. Suggestions for alternative ways to measure…

This article examines how rigour is achieved in the Abductive Research Strategy (ARS). It begins with a review of some of the arguments about objectivity and rigour in social sciences, which shows that quantitative and qualitative researchers hold different meanings of objectivity and therefore different ways of achieving rigour in their research.…

In this article, we consider the use of the zero-truncated binomial distribution as a randomization device while estimating the population proportion of a sensitive characteristic. The resultant new estimator based on the zero-truncated binomial distribution is then compared to its competitors from both the efficiency and the protection point of…

This study aims to address a gap in the social and behavioral sciences literature concerning interaction effects between latent factors in multiple-group analysis. By comparing two approaches for estimating latent interactions within multiple-group analysis frameworks using simulation studies and empirical data, we assess their relative merits.…

Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this article, we present a simple-to-use method for generating multiple imputations (MIs) using a Gaussian copula. The…

This article introduces an open-source software package--R for Qualitative Data Analysis (RQDA). RQDA is an R package for analysis of text-formatted data, which is compatible across operating platforms. It is user-friendly and seamlessly integrates with R, which makes it possible to conduct statistical analyses on qualitative coding. Alternative…

The use of quantitative methods within realist methodologies are fairly rare. This is perhaps because a realist understanding of the social word as complex and dynamic (messy but not chaotic) does not sit well with traditional variable-based causal analysis which test specific theoretical assumptions, yet cannot account for interaction, moderation…

Most of the social science research is based on the implied assumption that measurement error is the same across key socio-demographic groups and all differences in key statistics of interest are real. Nevertheless, there is evidence that this is not the case. In this paper, the authors tackle this important topic by investigating if data quality…

An important topic in the study of segregation are comparisons across space and time. This article extends current approaches in segregation measurement by presenting a five-term decomposition procedure that can be used to understand more clearly why segregation has changed or differs between two comparison points. Two of the five terms account…

Inequality often appears in linked pairs of variables. Examples include schooling and income, income and consumption, and wealth and happiness. Consider the famous words of Veblen: "wealth confers honor." Understanding inequality requires understanding input inequality, outcome inequality, and the relation between the two--in both…

Regression is one of the dominant analysis methods used in the social sciences and educational sciences. There are different regression methods based on the type of research that is being conducted. The probit and logit regression models are regression methods which are being used recently by most researchers. However, their interpretations are…