Suppose a researcher has done a 3x2x2 factorial study what does it mean

 A 3×2×2 factorial study refers to a research design involving three independent variables (factors), where:

  • The first factor has 3 levels

  • The second factor has 2 levels

  • The third factor also has 2 levels

Meaning:

This kind of study allows the researcher to examine:

  1. Main effects of each factor (how each variable independently affects the dependent variable).

  2. Two-way interactions (e.g., how the first and second factor interact, etc.).

  3. Three-way interaction (how all three variables together affect the outcome).

Total number of experimental conditions:

Multiply the levels of all factors:
3 × 2 × 2 = 12 experimental groups or conditions

Example (hypothetical):

  • Factor 1 (Teaching Method): Lecture, Group Work, Online

  • Factor 2 (Study Time): Low, High

  • Factor 3 (Test Format): MCQ, Descriptive

In this case, the researcher would assess student performance across 12 combinations of teaching method, study time, and test format.

Comments

Post a Comment

Popular posts from this blog

Two-Step System GMM (Generalized Method of Moments)

 The Two-Step System GMM is a dynamic panel data estimation technique designed to address: Endogeneity of explanatory variables Unobserved heterogeneity (fixed effects) Autocorrelation and heteroskedasticity It improves upon simpler estimators (like OLS or FE) and is particularly useful when the model includes lagged dependent variables . ⚙️ System GMM: The Basics Developed by Arellano & Bover (1995) and Blundell & Bond (1998) , System GMM combines: Difference GMM (Arellano & Bond, 1991): First-differences the model to remove fixed effects and uses lagged levels as instruments . Level GMM (Blundell & Bond) : Uses lagged differences as instruments for the level equation to improve efficiency. 🧮 The Dynamic Panel Model A typical dynamic panel data model is: y i t = α y i t − 1 + β X i t + μ i + ε i t y_{it} = \alpha y_{it-1} + \beta X_{it} + \mu_i + \varepsilon_{it} y i t ​ = α y i t − 1 ​ + β X i t ​ + μ i ​ + ε i t ​ Where: y...
Read more

Shodhganaga vs Shodhgangotri

  Shodhganga and Shodhgangotri are both initiatives by the INFLIBNET Centre (Information and Library Network Centre) in India. They aim to promote research and knowledge sharing in the academic community but serve different purposes. Here’s a comparison: Feature Shodhganga Shodhgangotri Purpose Repository for completed theses and dissertations. Repository for research proposals and synopses. Content Full-text doctoral theses and dissertations submitted by universities. Approved research proposals and synopses of doctoral students. Focus Stage of Research Final stage – after the research is completed. Initial stage – before the research begins. Target Audience Researchers looking for completed, peer-reviewed research work. Scholars looking for examples or ideas for research topics and methodologies. Utility ...
Read more

Panel Stationarity Tests: CADF and CIPS Explained

 When dealing with panel data , testing for stationarity (i.e., whether variables have a constant mean and variance over time) is crucial before estimation—especially in macroeconomic and financial studies. Two advanced second-generation panel unit root tests used to check for stationarity while accounting for cross-sectional dependence are: 🔹 1. CADF (Cross-sectionally Augmented Dickey-Fuller) Test 📌 Developed by: Pesaran (2007) CADF is an extension of the Augmented Dickey-Fuller (ADF) test that augments each ADF regression with cross-sectional averages to account for cross-sectional dependence . 🔍 Model Form: For each unit i i i , the CADF regression is: Δ y i t = a i + b i y i , t − 1 + c i y ˉ t − 1 + d i Δ y ˉ t + ∑ j = 1 p ϕ i j Δ y i , t − j + ε i t \Delta y_{it} = a_i + b_i y_{i,t-1} + c_i \bar{y}_{t-1} + d_i \Delta \bar{y}_{t} + \sum_{j=1}^{p} \phi_{ij} \Delta y_{i,t-j} + \varepsilon_{it} Δ y i t ​ = a i ​ + b i ​ y i , t − 1 ​ + c i ​ y ˉ ​ t − 1 ​ + d i ...
Read more