psystats

Basic statistics and biostatistics for psychologists, with an R-like functional API. Part of the ANOVA Methods family (psystats, psymetrics, psyreport).

Free and open (MIT). Every function returns a result object that prints an R-style summary and can be handed to psyreport.report() for APA-7 output.

Install

pip install psystats

What's inside

Descriptives and tables — describe, freq, corr_matrix (correlation matrix with significance stars), and table1 (group comparison with automatic test selection by variable type and distribution).

Inferential tests with effect sizes — ttest (Cohen's d), anova (η² and ω²), chisq (Cramér's V).

Regression — linreg (OLS with standardized betas, R²/adjusted R², F test) and logreg (odds ratios with confidence intervals, McFadden pseudo-R²).

Risk factors — riskratio, oddsratio, and attributable_risk (risk difference with CI, attributable risk percent, population attributable risk and PAR%, number needed to treat).

Example

The package ships a real teaching dataset — depression and anxiety symptoms in 1,957 undergraduate students from Spain, Portugal, and Brazil (Afonso Junior et al., 2020, https://doi.org/10.1590/0102.3772e36412) — so every example runs as-is:

from psystats import load_mapfre, table1, anova, corr_matrix, linreg

df = load_mapfre()

print(table1(df, group="country",                # auto test per variable
             columns=["age", "sex", "bdi_sum", "bai_sum"]))
print(anova(df, "bdi_sum", "country"))           # depression across countries
print(corr_matrix(df, ["age", "bdi_sum", "bai_sum"]))
print(linreg(df, "bdi_sum", ["age", "bai_sum"])) # predict depression score

All estimates are validated in the test suite against scipy and statsmodels.