George Choueiry

I am George Choueiry, PharmD, MPH, my objective is to help you conduct studies, from conception to publication.

Experimental vs Quasi-Experimental Design: Which to Choose?

Here’s a table that summarizes the similarities and differences between an experimental and a quasi-experimental study design:   Experimental Study (a.k.a. Randomized Controlled Trial) Quasi-Experimental Study Objective Evaluate the effect of an intervention or a treatment Evaluate the effect of an intervention or a treatment How participants get assigned to groups? Random assignment Non-random assignment …

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Correlation vs Collinearity vs Multicollinearity

Here’s a table that summarizes the differences between correlation, collinearity and multicollinearity:   Correlation Collinearity Multicollinearity Definition Correlation refers to the linear relationship between 2 variables Collinearity refers to a problem when running a regression model where 2 or more independent variables (a.k.a. predictors) have a strong linear relationship Multicollinearity is a special case of …

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Standardized vs Unstandardized Regression Coefficients

Here’s a table that summarizes the similarities and differences between standardized and unstandardized linear regression coefficients:   Unstandardized β Standardized β Definition Unstandardized coefficients are obtained after running a regression model on variables measured in their original scales Standardized coefficients are obtained after running a regression model on standardized variables (i.e. rescaled variables that have …

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Neyman’s [Prevalence-Incidence] Bias: A Simple Explanation

Neyman’s bias, also known as prevalence-incidence bias, occurs when studying the relationship between an exposure and an outcome using prevalence of the outcome instead of incidence in cases where prevalence is a biased estimator of incidence. Reminder:Prevalence is the proportion of individuals who have the outcome/disease at a given time.Incidence (or risk) is the number …

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Temporal Bias in Research

Temporal bias occurs when we assume a wrong sequence of events which misleads our reasoning about causality. It mostly affects study designs where participants are not followed over time. The most common study designs that are subject to temporal bias are: Cross-sectional studies: Because information is collected at a single moment in time Case-control studies: …

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Which Variables Should You Include in a Regression Model?

When building a linear or logistic regression model, you should consider including: However, you should watch out for: Below we discuss each of these points in details. 1. Selecting variables based on background knowledge Advantages of using background knowledge to select variables How to choose variables based on background knowledge? You can find out whether …

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