Missing Data Reporting Assistant
Turns your data cleaning process into a STROBE paragraph
Missing Data Reporting Assistant
Turns your data cleaning process into a STROBE paragraph
展示內容
描述
When you enter your sample size, missing data proportion/pattern (MCAR/MAR/MNAR), missing data method (listwise deletion, multiple imputation, etc.), and outlier detection method (Z-score, IQR, Mahalanobis), it produces an academic paragraph that can be inserted directly into the "Data Pre-processing" section of your manuscript. If there is a methodological contradiction between your method choice and the missing data pattern (e.g., using listwise deletion under an MNAR pattern), it states this explicitly. Suitable for: graduate students and researchers doing survey/clinical data analysis who want to write the data pre-processing section quickly and correctly.
為什麼我們推薦這個技能
An editor’s pick for turning messy cleaning decisions into a reviewer-ready STROBE data pre-processing paragraph. It stands out by checking numerical consistency, aligning missing-data methods with assumptions, and flagging how exclusions affect statistical power.
相關技能
查看全部
研究STROBE Methods Writer
Based on your cross-sectional, cohort, or case-control study design; when you enter your participant selection method, variables, sample size rationale, and statistical methods, it produces a complete Methods and Results draft with implicit reference to all 22 items of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist. It also provides a mapping table at the end showing which paragraph corresponds to which STROBE item — ready to answer a journal's "please complete the STROBE checklist" request. Avoids causal language (uses "is associated with" rather than "causes" for observational studies) and explicitly discusses sources of bias/confounding. Suitable for academics working in epidemiology, public health, and clinical research.
研究Meta-Analysis Full Report Writer
Produces a complete Methods + Results + Limitations text compliant with PRISMA 2020 and the Cochrane Handbook from your meta-analysis statistics (pooled effect size, I², Q, tau², publication bias indicators). Never misinterprets the I² value (including the "percentage of variance" framing); avoids overstated causal language (uses cautious phrasing like "findings are consistent with..." instead of "evidence demonstrates that"). At the end, it also offers at least 3 questions a reviewer might ask along with defense sentences. Suitable for: researchers writing a meta-analysis paper who want to strengthen the methods section before journal submission. What it does not do: it does not perform statistical calculations from raw data (you must already have your R/RevMan/CMA output) — it only converts and interprets your results into academic text.
研究CONSORT 2010 Report Writer
From your randomized controlled trial (RCT) data — randomization method, blinding status, power analysis, CONSORT flow numbers (screened/randomized/allocated/analyzed), ITT/PP analysis approach — it produces a complete Abstract + Methods + Results draft compliant with all 25 items of CONSORT 2010. It never confuses ITT/PP; it checks the consistency of flow diagram numbers (randomized ≥ allocated ≥ followed-up ≥ analyzed). It also pre-identifies at least 4 objections journal reviewers frequently raise (e.g., "why wasn't an ITT analysis reported," "was blinding success tested," "was there outcome switching") and suggests a defense sentence for each. Designed for clinical researchers in medicine/nursing/pharmacy conducting RCTs who want methodological robustness before journal submission. What it does not do: it does not perform statistical analysis or generate data — it only converts results you already have into a CONSORT-standard report.
