Study Design

7 Different Ways to Control for Confounding

Confounding can be controlled in the design phase of the study by using: Random assignment Restriction Matching Or in the data analysis phase by using: Stratification Regression Inverse probability weighting Instrumental variable estimation Here’s a quick summary of the similarities and differences between these methods: Study Phase Method Can easily control for multiple confounders Can …

7 Different Ways to Control for Confounding Read More »

List of All Biases [Sorted by Popularity in Research Papers]

I analyzed the content of 98,709 randomly chosen research papers from PubMed to learn more about bias. Specifically, I wanted to do 2 things: Rank 64 types of biases by popularity, in order to determine on which ones professional researchers focus the most in practice. Test the hypothesis that addressing bias issues is a sign …

List of All Biases [Sorted by Popularity in Research Papers] Read More »

Matched Pairs Design vs Randomized Block Design

In a matched pairs design, treatment options are randomly assigned to pairs of similar participants, whereas in a randomized block design, treatment options are randomly assigned to groups of similar participants. The objective of both is to balance baseline confounding variables by distributing them evenly between the treatment and the control group. Matched pairs design …

Matched Pairs Design vs Randomized Block Design Read More »

Randomized Block Design vs Completely Randomized Design

A randomized block design differs from a completely randomized design by ensuring that an important predictor of the outcome is evenly distributed between study groups in order to force them to be balanced, something that a completely randomized design cannot guarantee. A Completely randomized design uses simple randomization to assign participants to different treatment options …

Randomized Block Design vs Completely Randomized Design Read More »

Pretest-Posttest Control Group Design: An Introduction

The pretest-posttest control group design, also called the pretest-posttest randomized experimental design, is a type of experiment where participants get randomly assigned to either receive an intervention (the treatment group) or not (the control group). The outcome of interest is measured 2 times, once before the treatment group gets the intervention — the pretest — …

Pretest-Posttest Control Group Design: An Introduction Read More »

Separate-Sample Pretest-Posttest Design: An Introduction

The separate-sample pretest-posttest design is a type of quasi-experiment where the outcome of interest is measured 2 times: once before and once after an intervention, each time on a separate group of randomly chosen participants. The difference between the pretest and posttest measures will estimate the intervention’s effect on the outcome. The intervention can be: …

Separate-Sample Pretest-Posttest Design: An Introduction Read More »

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 …

Experimental vs Quasi-Experimental Design: Which to Choose? Read More »

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 …

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

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: …

Temporal Bias in Research Read More »