Contents
How many participants are needed for a logistic regression?
Dear researchers, in real world, a “reasonable” sample size for a logistic regression model is: at least 10 events (not 10 samples) per independent variable.
How many variables can you use in logistic regression?
There must be two or more independent variables, or predictors, for a logistic regression. The IVs, or predictors, can be continuous (interval/ratio) or categorical (ordinal/nominal).
How do you find the sample size for a logistic regression?
For logistic regression analysis, sample size is typically expressed in terms of events per variable (EPV), defined by the ratio of the number of events, i.e. number of observations in the smaller of the two outcome groups, relative to the number of degrees of freedom (parameters) required to represent the predictors …
What should the group size be in logistic regression?
We recommend using a minimum group size of 50 with at least 50 groups to produce valid estimates for multi-level logistic regression models. Group size should be adjusted under conditions where the prevalence of events is low such that the expected number of events in each group should be greater than one.
When to use a multilevel logistic regression model?
In this paper simulation studies based on multilevel logistic regression models are used to assess the impact of varying sample size at both the individual and group level on the accuracy of the estimates of the parameters and their corresponding variance components.
How are simulation studies used in logistic regression?
In this paper simulation studies are used to assess the effect of varying sample size at both the individual and group level on the accuracy of the estimates of the parameters and variance components of multilevel logistic regression models.
How is logistic regression used in medical research?
Logistic regression is one of the most utilised statistical analyses in multivariable models especially in medical research.