Table 1.

 Quantitative methods of research

Type	Description	Examples	Related literature
Descriptive	Focuses on the how/what/when/where, rather than the why	Classification of recovery criteria; examining aspects of recovery definitions	Couturier and Lock [69]
Comparative	Procedure to conclude one variable is better than another	Surveys of recovery definitions; comparing different definitions for agreement	Ackard et al. [70]
Univariate analyses	Statistical characteristics of a single variable	Statistics include distribution, central tendency, spread
Dichotomous variables	Yes/No variables; entered into Chi Square	Differences between recovery groups on a single measure	deVos et al. [33]
Continuous variables	Range variables; entered into t-tests and ANOVA	Severity of symptoms in recovery; differences between recovery groups on multiple measures	Cogley and Keel [71]
Bivariate analyses	Determines empirical relationship between two variables (X and Y)	Statistics include correlation coefficient (r); U statistic
Parametric	Evenly distributed data; entered into Pearson correlations	Ratings of recovery attitudes, stigma, self-esteem; relationships between recovery attitudes and related variables	Dimitropoulos et al. [72]
Non-parametric	Non-evenly distributed data; entered into Mann–Whitney–Wilcoxin or U-test	Comparing recovery groups to healthy controls	Ackard et al. [70]
Multivariate analyses	Determines best combination of all possible variables to test study hypothesis	Types of analyses: MANOVA, regressions, factor analysis, survival analysis, GEE (categorical outcomes), HLM (continuous outcomes)
MANOVA	Determines best combination of all categorical outcome variables	Comparing recovery and healthy control groups across different recovery scores	Bachner-Melman et al. [73]

ANOVA  analysis of variance, GEE  generalized estimating equations, HLM hierarchical linear models, MANOVA  multivariate analysis of variance