Unified estimation, diagnostics, and reporting for ordinary least 
    squares (OLS) regression, ANOVA/t-tests, logistic regression, panel data 
    (fixed/random effects with Hausman test), instrumental variables (2SLS with 
    weak instrument diagnostics), and difference-in-differences. Designed for 
    applied researchers in social sciences with integrated "Methodological Customs" 
    that audit assumptions and provide literature references. All methods 
    implemented in pure base R without external dependencies beyond stats and 
    graphics packages.

Tools designed to make it easier for users, particularly beginner/intermediate R users 
    to build ordinary least squares regression models. Includes comprehensive regression output, 
    heteroskedasticity tests, collinearity diagnostics, residual diagnostics, measures of influence, 
    model fit assessment and variable selection procedures.

The 'OLStrajr' package provides comprehensive functions for ordinary
    least squares (OLS) trajectory analysis and case-by-case OLS regression as
    outlined in Carrig, Wirth, and Curran (2004) <doi:10.1207/S15328007SEM1101_9>
    and Rogosa and Saner (1995) <doi:10.3102/10769986020002149>. It encompasses two
    primary functions, OLStraj() and cbc_lm(). The OLStraj() function simplifies
    the estimation of individual growth curves over time via OLS regression, with
    options for visualizing both group-level and individual-level growth trajectories
    and support for linear and quadratic models. The cbc_lm() function facilitates
    case-by-case OLS estimates and provides unbiased mean population intercept and
    slope estimators by averaging OLS intercepts and slopes across cases. It further
    offers standard error calculations across bootstrap replicates and computation
    of 95% confidence intervals based on empirical distributions from the resampling
    processes.

A tidy, long-format dataset of every athlete-event participation
    in the modern Olympic Games, spanning Athens 1896 through Milano-Cortina
    2026 (about 315,000 rows). Extends the rgriff23 'Olympic_history' dataset
    (1896-2016) with five additional editions scraped from Olympedia
    (<https://www.olympedia.org>):
    PyeongChang 2018, Tokyo 2020, Beijing 2022, Paris 2024, and
    Milano-Cortina 2026. Companion datasets cover edition-level metadata
    and verified medal tables for every edition from 1896 to 2026.