Nazarbayev University LibGuides: SPSS for Beginners: Selecting Appropriate Statistical Methods for Data Analysis

What Statistical Method I Should Use?

There are several statistical methods that you can use in analyzing your data. Incorrect selection of statistical methods may affect the potential outcome of the research study. Aside from knowledge of statistical methods, an understanding of the nature and type of the data collected and the objectives of the study is needed (Mishra et al., 2019).

Selecting the appropriate statistical methods depends on the following:

Aim and objective of the study
Type and distribution of the data used - understanding if the data is nominal, ordinal, or continuous. This also includes knowing the proportions, means etc.
Observations are paired or unpaired - to assess whether data is paired (same subjects are measures at different time points or using different methods) or unpaired (each group have different subjects).

Source: Mishra, P., Pandey, C. M., Singh, U., Keshri, A., & Sabaretnam, M. (2019). Selection of appropriate statistical methods for data analysis. Annals of cardiac anaesthesia, 22(3), 297–301. https://doi.org/10.4103/aca.ACA_248_18

PARAMETRIC VS. NON-PARAMETRIC METHODS (Mishra et al., 2019)

Inferential statistical methods fall into two possible categorizations:

Parametric method - statistical methods used to compare the means. It relies on the assumption that the variable is continuous and follows an approximate normally distributed.
Nonparametric method - statistical methods used to compare other than means (ex-median/mean ranks/proportions). When data is continuous with non-normal distribution or any other types of data other than continuous variable, nonparametric methods are used.

Image credit: Mishra, P., Pandey, C. M., Singh, U., Keshri, A., & Sabaretnam, M. (2019). Selection of appropriate statistical methods for data analysis. Annals of cardiac anaesthesia, 22(3), 297–301. https://doi.org/10.4103/aca.ACA_248_18

STATISTICAL METHODS TO COMPARE PROPORTIONS (NON-PARAMETRIC METHODS)

SEMI-PARAMETRIC AND NON-PARAMETRIC METHODS

Description	Statistical Method	Data Type
To predict the outcome variable using independent variables	Binary Logistic regression analysis	Outcome variable (two categories), Independent variable (s): Categorical (≥2 categories) or Continuous variables or both
To predict the outcome variable using independent variables	Multinomial Logistic regression analysis	Outcome variable (≥3 categories), Independent variable (s): Categorical (≥2 categories) or continuous variables or both
Area under Curve and cutoff values in the continuous variable	Receiver operating characteristics (ROC) curve	Outcome variable (two categories), Test variable : Continuous
To predict the survival probability of the subjects for the given equal intervals	Life table analysis	Outcome variable (two categories), Follow-up time : Continuous variable
To compare the survival time in ≥2 groups with P	Kaplan--Meier curve	Outcome variable (two categories), Follow-up time : Continuous variable, One categorical group variable
To assess the predictors those influencing the survival probability	Cox regression analysis	Outcome variable (two categories), Follow-up time : Continuous variable, Independent variable(s): Categorical variable(s) (≥2 categories) or continuous variable(s) or both
To predict the diagnostic accuracy of the test variable as compared to gold standard method	Diagnostic accuracy (Sensitivity, Specificity etc.)	Both variables (gold standard method and test method) should be categorical (2 × 2 table)
Absolute Agreement between two diagnostic methods	Unweighted and weighted Kappa statistics/Intra class correlation	Between two Nominal variables (unweighted Kappa), Two Ordinal variables (Weighted kappa), Two Continuous variables (Intraclass correlation)

Adopted from: Mishra, P., Pandey, C. M., Singh, U., Keshri, A., & Sabaretnam, M. (2019). Selection of appropriate statistical methods for data analysis. Annals of cardiac anaesthesia, 22(3), 297–301. https://doi.org/10.4103/aca.ACA_248_18