What types of statistical analysis are appropriate for a dissertation or thesis?
Multivariate statistics are usually appropriate but not exclusively used. I help graduate students everyday with dissertations and theses that utilize simple linear regressions, correlations, and t-tests, however, most institutions and committees want to see multivariate statistics used by their graduate students. That said, here is a very short list of the common ones.
Multiple regression for your dissertation or thesis will simply include more than one predictor. The advantage to using this statistical test for your dissertation or thesis is that you include multiple variables in your model predicting your variable of interest. Very rarely – if ever – is it the case that only one variable is responsible for values of another variable. I like an example using the Super Bowl. I may be able to predict a good percentage of Super Bowl victories with salaries, but we all know there are many more factors involved in predicting Super Bowl victories, such as injuries, weather, experience, and strength of schedule. Including multiple predictors makes for a more accurate model. Get help with using multiple regressions for your Master's thesis, Master's dissertation, Ph.D. thesis, or Ph.D. dissertation.
The logic behind the multiple regression applies to the logistic regression, except that the logistic regression utilizes an odds ratio to predict the occurrence of a dichotomous variable. Get help with using logistic regressions for your Master's thesis, Master's dissertation, Ph.D. thesis, or Ph.D. dissertation.
n – way ANOVA (Analysis of Variance) or Factorial ANOVA(Analysis of Variance)
The n in this case is simply referring to the virtually limitless number of independent variables that can be used in an ANOVA. A two-way ANOVA is the equivalent of conducting two ANOVAs or t-tests in one test and is simply a factorial ANOVA. A factorial ANOVA is just an ANOVA with two or more independent variables. An n-way ANOVA or factorial ANOVA could have three, four, five, or more independent variables. This method also allows for not just testing of differences between the groups but also testing of interactions between the independent variables. Get help with n-way ANOVA factorial ANOVA for your Master's thesis, Master's dissertation, Ph.D. thesis, or Ph.D. dissertation.
Mixed ANOVA(Analysis of Variance)
Again, the logic behind this test is the same as the n-way ANOVA or factorial ANOVA, but is the equivalent of conducting:
- a dependent samples t-test or paired samples t-test and an independent samples t-test or two sample t-test at the same time.
- a repeated measures ANOVA and simple ANOVA at the same time.
The complexity of the test depends completely on the number of variables involved in the statistical analysis. The effect of conducting a mixed ANOVA is the increase in power from conducting multiple statistical tests in one test, while protecting your alpha in the process. Get help with using mixed ANOVA for your Master's thesis, Master's dissertation, Ph.D. thesis, or Ph.D. dissertation.
MANOVA (Multivariate Analysis of Variance)
The same logic again, except this time we are analyzing multiple dependent variables. For example, we may want to test for significant differences in GPA, SAT scores, and ACT scores, by religious affiliation. We can do all of these comparisons at the same time in the same test with the MANOVA or multivariate analysis of variance. This is a favorite of many a professional researcher and committee. Get help with using MANOVA or multivariate analysis of variance for your Master's thesis, Master's dissertation, Ph.D. thesis, or Ph.D. dissertation.
ANCOVA (Analysis of Covariance) MANCOVA (Multivariate Analysis of Covariance
These have the same benefits and accomplish the same thing as their siblings without the "C" or "Co" but add that capability of excluding variables that could somehow invalidate your results. To do this, the ANCOVA and the MANCOVA utilize a control variable. For example, if I wanted to know if there is a significant difference in GPA between college students, there could be any number of factors that could cause the difference. But by isolating the effect those factors have on my test, I am able to test for real differences. In this case I might control for socioeconomic status and the number of extracurricular activities. Utilizing the control variable will do a great deal to silence the critics of your research that may attribute the differences you found to the existence of some extraneous, unidentified, and unaccounted for variable. Get help with using ANCOVAs (analysis of covariance) or MANCOVAs (multivariate analysis of covariance) for your Master's thesis, Master's dissertation, Ph.D. thesis, or Ph.D. dissertation.
Doubly Multivariate Analysis of Covariance
I just thought I would throw this in here to get you thinking a little about what's possible. If your head's spinning at this point, click here and I will be more than happy to help you with your statistics for your dissertation or thesis.