We help you plan analyses, validate assumptions, and present results that meet university and journal standards complete with reproducible code and submission-ready figures/tables.
Distributions, outliers, transformations, visualization.
t-tests, ANOVA/ANCOVA, χ², non-parametrics with post-hoc.
Linear/logistic/Poisson/negative-binomial; interactions & diagnostics.
Repeated/clustered data (LMM/GLMM), random effects.
Multivariate tests with assumptions & follow-ups.
Pearson/Spearman; PCA for dimension reduction.
Path models/CFA (intro), fit indices, modification checks (cautious).
Prospective power, detectable effect sizes, attrition.
| Area | Examples | Notes |
|---|---|---|
| Assumptions | Normality, homoscedasticity, independence | Diagnostics & remedies reported |
| Effect sizes | d, r, η²/η²p, OR/RR | With confidence intervals |
| Multiple tests | Bonferroni, Holm, FDR | Control family-wise or FDR as needed |
| Missing data | MCAR/MAR/MNAR | Imputation/sensitivity as scope allows |
| Reproducibility | Scripts, notebooks | Versioned, commented, change log |
| Reporting | APA/AMA/IEEE | Journal/conference specific styling |
All choices (tests, corrections, models) are documented for transparent defense.
EDA + assumptions + quick tests + 2–3 figures/tables + notes.
Full analysis + diagnostics + 4–6 figures/tables + write-up.
Mixed models/intro SEM + robust checks + manuscript polish.
Pricing varies with data quality, model complexity, and turnaround. You’ll receive a clear plan after discovery.
Aims, variables, design, style guide/journal requirements.
Analysis plan + milestones + deliverables.
Cleaning, codebook, missing-data plan, backups.
Primary & sensitivity analyses with diagnostics.
Figures/tables + Methods/Results text.
Scripts/notebooks, outputs, and change log.
Yes we align tests/models to your question, design, and measurement scales, and explain the trade-offs.
Absolutely diagnostics are standard; we use robust or non-parametric alternatives when needed.
Yes. We report effect sizes with confidence intervals for interpretability.
We apply corrections (e.g., Holm/FDR) and explain the rationale in the write-up.
Yes prospective power/sample size or detectable effect size based on your design.
You receive all scripts/notebooks, plus a cleaned dataset when permitted.
DOCX, PDF, LaTeX for documents; CSV/XLSX/Parquet for data; R/Py/SPSS/Stata scripts.
Yes LMM/GLMM with random effects and appropriate covariance structures.
Small tasks: days; chapters/manuscripts: weeks with milestones agreed at kickoff.
By scope, data condition, model complexity, and turnaround. You’ll get a clear quote after discovery.