Table 1

Comparison of linear, logistic and multiple regression

 Linear Logistic Multiple Purpose Examines the relationship between one independent variables with one dependent continuous variable Calculates the likelihood of event with binary outcome (ie, yes or no) It is an extension of simple linear regression and examines the relationship between one or more independent and dependent variables simultaneously Nature of dependent and independent variables Dependent variable should be continuousIndependent variables could be at any level of measurement Dependent variable should be categorialIndependent variables could be at any level of measurement Dependent variables should be continuousIndependent variables could be at any level of measurement Assumptions Assumes that the distribution of dependent data is normal or GaussianRequires a linear relationship between dependent and independent variables Assumes that the distribution of dependent data is binomial.It does not require a linear relationship between dependent and independent variablesThe independent variables should not be correlated Assumes that the distribution of dependent data is normal or GaussianRequires a linear relationship between dependent and independent variablesThe independent variables should not be correlated. Higher correlation among the independent variables may affect the relationship between independent and dependent variable Nature of curve It uses a straight line It uses an S-curve It uses a straight line Example Examining the relationship between hours of training and levels of patient self-care and predict how long training should last for every unit increase in self-care levels Estimating the likelihood of development of pressure ulcers (dichotomous outcome: yes or no) due to longer hospital stay, number of times of positioning, BMI (Body Mass Index) and age Examining the relationship between hours of training and patient self-care levels while controlling for other variables (eg, family support, duration of disease) that may affect the relationship