Table 1  Quantitative methods of research

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]