Interview somebody that has or had a career in the retail field. You can meet them in person or if time does not permit email them. Ask at least two of the questions that interest you from the list below:
Interview somebody that has or had a career in the retail field. You can meet them in person or if time does not permit email them. Ask at least two of the questions that interest you from the list below: What is an average day like in your position? What are some of your primary […]
Difference between Factor Analysis and Path Analysis
Factor analysis and path analysis are both statistical techniques used in the field of multivariate analysis, particularly in the context of structural equation modeling (SEM). While they share some similarities, they serve different purposes and have distinct methodologies. Factor Analysis: Purpose: Factor analysis is primarily used to identify underlying factors or latent variables that explain […]
Methods of Conducting Mediation Analysis – Using Regression Analysis
How to Testing Mediation Analysis with Regression Analysis Mediation analysis is a hypothesized causal chain in which one variable affects a second variable that, in turn,affects a third variable. The intervening variable, M, is the mediator. It “mediates” the relationship between a predictor, X, and an outcome. Graphically, mediation can be depicted in the following […]
Testing Mediation Analysis with Regression Analysis
How to Testing Mediation Analysis with Regression Analysis Mediation analysis is a hypothesized causal chain in which one variable affects a second variable that, in turn,affects a third variable. The intervening variable, M, is the mediator. It “mediates” the relationshipbetween a predictor, X, and an outcome. Graphically, mediation can be depicted in the following way: […]
Probit and Logit Models (Binary Outcome Models)
Probit and Logit models are binary outcome models used to predict the probability of an event occurring. The dependent variable in these models is a binary response, commonly coded as a 0 or 1 variable. The linear probability model is also discussed, but it has the clear drawback of not being able to capture the […]
How to Do Propensity Score Matching
Propensity Score Matching in Stata using teffects Note: readers interested in this article should also be aware of King and Nielson’s 2019 paper Why Propensity Scores Should Not Be Used for Matching. For many years, the standard tool for propensity score matching in Stata has been the psmatch2 command, written by Edwin Leuven and Barbara Sianesi. However, Stata […]
Propensity Score Matching – An Introduction
Propensity score matching is a non-experimental causal inference technique. It attempts to balance the treatment groups on confounding factors to make them comparable so that we can draw conclusions about the causal impact of a treatment on the outcome using observational data. This is important when AB testing is not feasible or simply not an option. In this […]
Propensity score matching (PSM) – STATA
Propensity score matching (PSM) is a quasi-experimental method in which the researcher uses statistical techniques to construct an artificial control group by matching each treated unit with a non-treated unit of similar characteristics. Using these matches, the researcher can estimate the impact of an intervention. Matching is a useful method in data analysis for estimating the impact of a program […]
What is Structural Equation Modeling (SEM) analysis?
Structural Equation Modeling (SEM) analysis is a statistical method used in social science studies for testing the linkage between multiple variables at any point in time. SEM analysis is an extension of the simple linear model. For example, there are many factors that affect the organizational commitment and the job satisfaction level of an employee. If the impact […]
How to perform panel data analysis in E-Views?
E- Views offer an impressive toolkit that involves the series or the group of series that allows estimating panel data analysis ranging from the simplest to the complex types. Performing data analysis in E-views is easier to understand as all the necessary statistical modelling can be performed by estimating the regression equation. In addition to this, E-views […]
