- The choice of statistical methods depends on the research
question, the scales on which the variables are measured, and the
number of variables to be analyzed.
- Many of the advanced statistical procedures can be interpreted
as an extension or modification of multiple regression analysis.
- Many of the statistical methods used for questions with one
independent variable have direct analogies with methods for multiple
- The term “multivariate” is used when more
than one independent variable is analyzed.
- Multiple regression is a simple and ideal method to control
for confounding variables.
- Multiple regression coefficients indicate whether the relationship
between the independent and dependent variables is positive or negative.
- Dummy, or indicator, coding is used when nominal variables
are used in multiple regression.
- Regression coefficients indicate the amount the change in
the dependent variable for each one-unit change in the X variable,
holding other independent variables constant.
- Multiple regression measures a linear relationship only.
- The Multiple R statistic is the best indicator of how well
the model fits the data—how much variance is accounted
- Several methods can be used to select variables in a multivariate
- Polynomial regression can be used when the relationship is
- Cross-validation tell us how applicable the model will be
if we used it in another sample of subjects.
- A good rule of thumb is to have ten times as many subjects
- Analysis of covariance controls for confounding variables;
it can be used as part of analysis of variance or in multiple regression.
- Logistic regression predicts a nominal outcome; it is the
most widely used regression method in medicine.
- The regression coefficients in logistic regression can be
transformed to give odds ratios.
- The Cox model is the multivariate analogue of the Kaplan–Meier
curve; it predicts time-dependent outcomes when there are censored
- The Cox model is also called the proportional hazard model;
it is one of the most important statistical methods in medicine.
- Meta-analysis provides a way to combine the results from several
studies in a quantitative way and is especially useful when studies
have come to opposite conclusions or are based on small samples.
- An effect size is a measure of the magnitude of differences
between two groups; it is a useful concept in estimating sample
- The Cochrane Collection is a set of very well designed meta-analyses
and is available at libraries and online.
- Several methods are available when the goal is to classify
subjects into groups.
- Multivariate analysis of variance, or MANOVA, is analogous
to using ANOVA when there are several dependent variables.
In Chapter 8 we examined the study by Jackson and colleagues
(2002) who evaluated the relationship between BMI and percent body
fat. Please refer to that chapter for more details on the study. We
found a significant relationship between these two measures and
calculated a correlation coefficient of r = 0.73. These
investigators knew, however, that variables other than BMI may also ...