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計画
Design of Experiments Worksheet Template (Statistics, R and Python)
フルPlan an experiment before running it: CRD, randomised block, Latin square, 2^k factorial, fractional factorial, centre points, seeded run order in R and Python
Fisher (1935); Box, Hunter and Hunter (2005); Box and Hunter (1961); NIST/SEMATECH e-Handbook ch. 5Power Analysis and Sample Size Template (Statistics, R and Python)
フルPower analysis and sample size worksheet: t-tests, proportions, ANOVA, correlation, regression, simulation power, sensitivity table and justification sentence
Cohen (1988); Lakens (2022) sample size justification; Hoenig and Heisey (2001); pwr 1.3.0 and statsmodels 0.15.0Experiment Protocol Template
標準Protocol – materials, controls, KaTeX stats
Study Preregistration Template
標準Preregistration of hypotheses, design, sampling plan and stopping rule, variables, analysis plan, exclusions and deviations log
OSF preregistration (concepts)
手法とパターン
One-Way ANOVA Method Card Template (Statistics, R and Python)
フルClassic and Welch one-way ANOVA, ANOVA table by hand, Tukey HSD, Games-Howell, planned contrasts, eta squared with CI and omega squared
Fisher (1925); Welch (1951); Tukey (1949); Games and Howell (1976); Hays (1963); Steiger (2004); NIST/SEMATECH e-Handbook 7.4Factorial ANOVA Method Card Template (Statistics, R and Python)
フルTwo-way between-subjects ANOVA: main effects, interaction plot, simple effects with emmeans and statsmodels, type I/II/III sums of squares, partial eta squared
Fisher (1925, 1935); Yates (1934); Searle (1971); Langsrud (2003); Cohen (1973); NIST/SEMATECH e-Handbook 5.3 and 7.4Repeated-Measures ANOVA Method Card Template (Statistics, R and Python)
フルWithin-subject designs: repeated-measures ANOVA, sphericity, Greenhouse-Geisser and Huynh-Feldt, Friedman, Holm post hoc, split-plot overview, when to switch to mixed models
Fisher (1925); Mauchly (1940); Greenhouse and Geisser (1959); Huynh and Feldt (1976); Friedman (1937); Holm (1979); NIST/SEMATECH e-Handbook; APA JARS-Quant (name)ANCOVA Method Card Template (Statistics, R and Python)
フルAnalysis of covariance: covariate adjustment, homogeneity of slopes, adjusted means by hand and with emmeans, ANCOVA vs change scores, Lord's paradox, reporting
Fisher (1932); Lord (1967); Searle, Speed and Milliken (1980); Senn (2006); NIST/SEMATECH e-Handbook; APA JARS-Quant (name)Linear Mixed Models Method Card Template (Statistics, R and Python)
フルClustered and longitudinal data: random intercepts and slopes, ICC, REML vs ML, lme4 and statsmodels MixedLM side by side, df methods, singular fits, reporting
Laird and Ware (1982); Patterson and Thompson (1971); Satterthwaite (1946); Kenward and Roger (1997); Bates et al. (2015); NIST/SEMATECH e-Handbook; APA JARS-Quant (name)
検証
Assumption Checklist Template (Statistics, Diagnostics, R and Python)
フルChecking assumptions per method family (t/ANOVA, regression, GLMs, chi-square, correlation, repeated measures and mixed models): diagnostics, R and Python code, judgement rules and remedies
NIST/SEMATECH e-Handbook of Statistical Methods; Cook (1977); Box and Cox (1964); Levene (1960); Brown and Forsythe (1974); Mauchly (1940); Greenhouse and Geisser (1959); Nelder and Wedderburn (1972); Fox and Weisberg (2019)Effect Sizes Template (Statistics, Choice, Formulas, CIs, R and Python)
フルChoosing, computing and reporting effect sizes (d, g, d_z vs d_av, eta and omega squared, r, V, OR, RR, R squared, f squared) with CIs, conversions and R/Python code
Cohen (1988); Hedges (1981); Hedges and Olkin (1985); Olejnik and Algina (2003); Lakens (2013); Borenstein et al. (2009)