Minimum sample size for developing a multivariable prediction model using multinomial logistic regression
Alexander Pate; Richard D Riley; Gary S. Collins; Maarten van Smeden; Ben Van Calster; Joie Ensor; Glen P. Martin · 2023 · Statistical Methods in Medical Research
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Abstract
Aims Multinomial logistic regression models allow one to predict the risk of a categorical outcome with > 2 categories. When developing such a model, researchers should ensure the number of participants ([Formula: see text]) is appropriate relative to the number of events ([Formula: see text]) and the number of predictor parameters ([Formula: see text]) for each category k. We propose three criteria to determine the minimum n required in light of existing criteria developed for binary outcomes. Proposed criteria The first criterion aims to minimise the model overfitting. The second aims to
Abstract by Alexander Pate; Richard D Riley; Gary S. Collins; Maarten van Smeden; Ben Van Calster; Joie Ensor; Glen P. Martin, Statistical Methods in Medical Research (2023) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1177/09622802231151220