Related Experiment Video
Updated: Sep 22, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Untying the climate strength knot: A meta-analytic examination of restricted variance effects in climate strength
Kathleen R Keeler1, Balca Alaybek2, Jose M Cortina3
1Department of Management and Human Resources.
Abstract:
Climate strength is often included in organizational climate models, however, its role in such models remains unclear. We propose that the inconsistent findings regarding the effects of climate strength are due in part to its complicated relationship with climate level. Specifically, we propose that the relationship between level and strength is heteroscedastic and nonlinear due to restricted variance (RV) and potential leniency bias in climate ratings. We examine how this relationship between level and strength affects relations between climate strength and work-related outcomes, as well as the implications that this has for bilinear interactions between level and strength. In this meta-analysis, we analyzed 81 independent samples from 77 articles and find support for a heteroscedastic, curvilinear relationship between climate level and climate strength, consistent with the notion that variance compression and leniency bias are present in climate ratings. With regard to the three proposed roles of climate strength in organizational models, we find some support for an additive effect of strength on outcomes, but only at high levels of climate level, and little support for strength as a bilinear moderator of level-outcome relations or for strength as a nonlinear predictor of outcomes. We do find, however, some support for nonlinear interaction effects between level and strength. We discuss implications of our findings for the role of climate strength in future research and for multilevel theory in general. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
More Related Videos
Related Concept Videos
Variability: Analysis
The range is a simple measure of variability, indicating the difference between the highest and...
One-Way ANOVA: Equal Sample Sizes
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Friedman Two-way Analysis of Variance by Ranks
One-Way ANOVA
One-Way ANOVA: Unequal Sample Sizes
Calculating and Interpreting the Linear Correlation Coefficient

