Topic
Variables
About: Variables is a research topic. Over the lifetime, 10195 publications have been published within this topic receiving 448603 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: A tutorial is provided illustrating an approach to estimation of and inference about direct, indirect, and total effects in statistical mediation analysis with a multicategorical independent variable that reproduces the observed and adjusted group means while also generating effects having simple interpretations.
Abstract: Virtually all discussions and applications of statistical mediation analysis have been based on the condition that the independent variable is dichotomous or continuous, even though investigators frequently are interested in testing mediation hypotheses involving a multicategorical independent variable (such as two or more experimental conditions relative to a control group). We provide a tutorial illustrating an approach to estimation of and inference about direct, indirect, and total effects in statistical mediation analysis with a multicategorical independent variable. The approach is mathematically equivalent to analysis of (co)variance and reproduces the observed and adjusted group means while also generating effects having simple interpretations. Supplementary material available online includes extensions to this approach and Mplus, SPSS, and SAS code that implements it.
2,318 citations
TL;DR: The familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models are described and macros for SPSS and SAS are introduced to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression.
Abstract: Researchers often hypothesize moderated effects, in which the effect of an independent variable on an outcome variable depends on the value of a moderator variable. Such an effect reveals itself statistically as an interaction between the independent and moderator variables in a model of the outcome variable. When an interaction is found, it is important to probe the interaction, for theories and hypotheses often predict not just interaction but a specific pattern of effects of the focal independent variable as a function of the moderator. This article describes the familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models and introduces macros for SPSS and SAS to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression. A script version of the SPSS macro is also available for users who prefer a point-and-click user interface rather than command syntax.
2,204 citations
01 Jan 1994
TL;DR: The most important developments in econometrics in the past ten years have occurred in the area of qualitative response (QR) models as discussed by the authors, and there are two factors which explain the recent upsurge of QR models in economic applications: 1) Economists deal with many variables, thus necessitating the need to formulate more complex models involving more than one discrete variable and more than two responses, as well as using more independent variables.
Abstract: One of the most important developments in econometrics in the past ten years has occurred in the area of qualitative response (QR) models. There are two factors which explain the recent upsurge of QR models in economic applications: 1) Economists deal with many variables, thus necessitating the need to formulate more complex models involving more than one discrete variable and more than two responses, as well as using more independent variables. The estimation of such complex QR models has only recently been made possible by the development of advanced computer technology. 2) An increasingly large number of sample surveys have been recently conducted and their results made readily available on magnetic tapes. This paper will present the basic facts about QR models. It starts with the discussion of the simplest model - the model for a univariate dichotomous dependent variable, and then moves on to multi-response models. The following three problems are discussed: 1) how to specify a model which is consistent with economic theory and which is at the same time statistically manageable; 2) how to estimate and test hypotheses on the parameters of a model; and 3) what criteria to use for choosing among competing models.
1,995 citations
TL;DR: The authors argue that the focus in mediation analysis should be shifted towards assessing the magnitude and significance of indirect effects, arguing that the collective evidence raises considerable concern that focusing on the significance between the independent and dependent variables is unjustified and can impair theory development and testing.
Abstract: A key aim of social psychology is to understand the psychological processes through which independent variables affect dependent variables in the social domain. This objective has given rise to statistical methods for mediation analysis. In mediation analysis, the significance of the relationship between the independent and dependent variables has been integral in theory testing, being used as a basis to determine (1) whether to proceed with analyses of mediation and (2) whether one or several proposed mediator(s) fully or partially accounts for an effect. Synthesizing past research and offering new arguments, we suggest that the collective evidence raises considerable concern that the focus on the significance between the independent and dependent variables, both before and after mediation tests, is unjustified and can impair theory development and testing. To expand theory involving social psychological processes, we argue that attention in mediation analysis should be shifted towards assessing the magnitude and significance of indirect effects.
1,983 citations
Posted Content•
TL;DR: The most important developments in econometrics in the past ten years have occurred in the area of qualitative response (QR) models as discussed by the authors, and there are two factors which explain the recent upsurge of QR models in economic applications: 1) Economists deal with many variables, thus necessitating the need to formulate more complex models involving more than one discrete variable and more than two responses, as well as using more independent variables.
Abstract: One of the most important developments in econometrics in the past ten years has occurred in the area of qualitative response (QR) models. There are two factors which explain the recent upsurge of QR models in economic applications: 1) Economists deal with many variables, thus necessitating the need to formulate more complex models involving more than one discrete variable and more than two responses, as well as using more independent variables. The estimation of such complex QR models has only recently been made possible by the development of advanced computer technology. 2) An increasingly large number of sample surveys have been recently conducted and their results made readily available on magnetic tapes. This paper will present the basic facts about QR models. It starts with the discussion of the simplest model - the model for a univariate dichotomous dependent variable, and then moves on to multi-response models. The following three problems are discussed: 1) how to specify a model which is consistent with economic theory and which is at the same time statistically manageable; 2) how to estimate and test hypotheses on the parameters of a model; and 3) what criteria to use for choosing among competing models.
1,971 citations