Research Resources
Selecting a Statistical Test

Many of the examples do not show the screening of data or address the assumptions of the model. My intent was to focus on the major analyses, but these issues are EXTREMELY important and should always be considered in your research.

 

Independent Variables

Dependent Variables

Test

Association/relationship

2 continuous variables

(no IV or DV designated)

Correlation Coefficient

  2 categorical variables (no IV or DV designated) Chi-Square
  1 IV 1 DV (continuous) Simple Regression
  2 or more variables 1 DV (continuous) Multiple Regression (standard)
  2 or more variables (theory) 1 DV (continuous) [Hierarchical--Change in R2]
Multiple Regression (sequential)
  2 or more variables 2 or more variables Canonical Correlation

 

 

 

 

Group Differences

1 IV (2 groups)*

1 DV (continuous)

Independent t-test

 

1 IV (2 related groups)**

1 DV (continuous)

Dependent t-test

 

1 IV (3 or more groups)*

1 DV (continuous)

One-way ANOVA

 

2 IVs (both categorical)*

1 DV (continuous)

Two-way ANOVA

  2 IVs (both categorical but one repeating measures factor) 1 DV (continuous) Split Plot ANOVA
  2 IVs (both categorical but one repeating measures factor) Multiple DVs that are commensurate Profile Analysis
  2 IVs (both categorical but one with lots of repeating measures0 1 DV (continuous) that repeats (time-series) Generalized Estimating Equation (GEE)
  1 IV (categorical) 1 DV (continous) and 1 Covariant ANCOVA

 

1 IV (2 groups)*

2 or more DVs (continuous)

MANOVA (Hotelling’s T)

 

1 IV (2 or more groups)*

2 or more DVs (continuous)

MANOVA (Wilks’ Lambda)

 

2 IVs (both categorical)*

2 or more DVs (continuous)

MANOVA (look for 3 tests)

  1 (or more) IVs (both categorical and repeating measures) Multiple DVs (continuous) at multiple times Doubly Multivariate Analysis
       
Predicting Group Membership 2 or more IVs (predictors) 1 DV (catgorical)  Discriminate Function Analysis
  2 or more variables 1 DV (binary outcome) Logistic Regression

 

 

 

 

Structural

No IVs or DVs

Exploratory Factor Analysis
    Exploratory Factor Analysis -
Annotated Output
    Confirmatory Factor Analysis
    Confirmatory Factor Analysis-LISREL
     
     
Screening Data - Univariate Univariate Screening Univariate Screening
Screening Data - MV Multivariate Screening  
Missing Data MVA in SPSS Missing Data MVA

 Note. *All these IVs are referred to as between subjects factors. **IV is a within subject factor.

Reporting Standards
[Standard for Reporting in Social Science]

Structural Equation Modeling
David Kenny (free book on correlational inferences)
http://davidakenny.net/cm/causalm.htm

Mixed Method
Article

Survey
Principles for Constructing Web Surveys

Other Resources
http://core.ecu.edu/psyc/wuenschk/SPSS/SPSS-MV.htm
http://lstat.kuleuven.be/newjava/vestac/
http://www.ruf.rice.edu/~lane/stat_sim/comp_r/index.html

Data List
http://www2.hawaii.edu/~daniel/Data/dir.html#467