Sample Sizes When Using Multiple Linear Regression for Prediction
Abstract
When using multiple regression for prediction purposes, the issue of minimum required sample size often needs to be addressed. Using a Monte Carlo simulation, models with varying numbers of independent variables were examined and minimum sample sizes were determined for multiple scenarios at each number of independent variables. The scenarios arrive from varying the levels of correlations between the criterion variable and predictor variables as well as among predictor variables. Two minimum sample sizes were determined for each scenario, a good and an excellent prediction level. The relationship between the squared multiple correlation coefficients and minimum necessary sample sizes were examined. A definite relationship, similar to a negative exponential relationship, was found between the squared multiple correlation coefficient and the minimum sample size. As the squared multiple correlation coefficient decreased, the sample size increased at an increasing rate. This study provides guidelines for sample size needed for accurate predictions.
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“Additionally, QCA is not burdened by the same sample size constraints that parametric statistics must navigate [38].”
Background
- Authors
- Knofczynski, G. T., & Mundfrom, D.
- Affiliations
- Armstrong Atlantic State University,
- University of Northern Colorado (US)
- Venue
- Educational and Psychological Measurement
- Publisher
- SAGE Publications
- Published
- 2007-11-09
- Volume
- 68
- Issue
- 3
- Pages
- 431-442
- ISSN
- 0013-1644 (ISSN-L)
- 1552-3888
- OpenAlex
- W2142640630
- Cited by
- 306
- References
- 26
- Citations by year
- 2026: 6 · 2025: 13 · 2024: 22 · 2023: 16 · 2022: 33 · 2021: 22 · 2020: 23 · 2019: 29 · 2018: 32 · 2017: 28 · 2016: 18 · 2015: 14 · 2014: 13 · 2013: 10 · 2012: 9
- FWCI
- 3.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Educational and Psychological Measurement (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- sample size determination, multiple linear regression, prediction, minimum sample size, squared multiple correlation, Monte Carlo simulation
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