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Logistic regression is a useful statistical technique to understand complex phenomena. The use of this statistic is discussed, along with how to understand research when it is used.
In this issue, Tzeng and colleagues (2020) used logistic regression to analyze social determinants as they relate to organizing personal healthcare self-care in older adults. Logistic regression is a useful statistical technique to understand complex phenomena. The use of this statistic is discussed, along with how to understand research when it is used.
Regression
Because logistic regression is a form of regression, it is important to understand the concepts of regression. Simple linear regression is a procedure used to estimate the value of a dependent variable (generally the variable of greatest interest) based on the value of the independent variable (Cipher, 2017). The premise is that plotting the variables on a scatter plot and then drawing a straight line through them provides the best fit through the plotted scores (linear relationship). Best fit means the line is drawn where the data are distributed equally on both sides of the line. This best fit line then represents the association between the two variables. The statistics involved predict the value of one variable if the value of the other variable is known. For example, this would be appropriate if the researcher wanted to predict patient satisfaction scores based on patient age.
Some assumptions exist for this statistical procedure. First, a normal distribution of the dependent variable is presumed. A linear relationship between the two variables also is supposed. Basically, this means when...