RISA — Research Intelligence & Statistical Analysis

1

Research Setup

Basic information used to personalise all generated prompts.

Research title / topic

Data type

Statistical software

AI assistant

Research field

Study context

2

Define Variables

Add the variables used in your study. Codes should match the names used in your statistical software.

Dependent Variables

Name	Code	Measurement / formula

Independent Variables

Name	Code	Measurement / formula

Mediators / Moderators

Role	Name	Code	Measurement / formula

Control Variables

Name	Code	Measurement / formula

3

Hypotheses

Enter your existing hypotheses or let the form structure them from the variables.

Auto-update hypotheses when variables changeNew IV–DV relationships are added automatically. Turn this off before making extensive manual edits.

No.	Hypothesis statement	Expected direction

4

Data Structure

These details help the generated prompt describe the dataset correctly.

Panel / entity identifier

Time variable

Observation level

Start year

End year

Panel balance

5

Data File & Working Folder

Tell the generated AI prompt how Stata should open the dataset, create logs, and save output files.

Stata data workflow

Working folder / project path

Existing Stata dataset

Exact .dta file name

Use this file automatically in each analysis block?

Stata log & output management

Log policy

Log file prefix

Where should exported results be saved?

Recommended Stata workflow: set the working directory with cd, safely close any open log, open the required log, load the required .dta file, run the stage commands, save/export requested results to the selected folder, then close the log.

File and log automation in Version 1.1 is currently designed for Stata. If EViews is selected, Stata-specific cd, use, and log instructions are omitted.

6

Analysis Plan

Select what the AI prompt should guide the researcher to perform in the statistical software.

A. Preliminary Analysis

Declare data structurePanel/entity and time settings.

Descriptive statisticsMean, median, SD, min, max and observations.

Skewness & kurtosisDistribution shape and potential outliers.

Correlation matrixInclude significance where appropriate.

VIFAssess multicollinearity.

Data treatment guidanceTransformation, winsorisation or trimming only when justified.

B. Parametric Tests Added

One-sample t-testCompare a sample mean with a benchmark.

Independent t-testCompare means across two independent groups.

Paired t-testCompare two related measurements.

One-way ANOVACompare means across three or more groups.

Two-way ANOVATwo categorical factors and interaction.

Welch alternativeUse when equal-variance assumptions are not appropriate.

Parametric test setup

Grouping variable (optional)

Test / benchmark value (optional)

The generated prompt asks the AI to check assumptions before recommending a parametric test and to avoid forcing a test that does not fit the study design.

C. Panel Regression & Model Selection

Pooled OLSBaseline pooled specification.

Fixed EffectsEntity fixed effects specification.

Random EffectsRandom-effects specification.

FE vs RE selectionUsually Hausman-type model selection when appropriate.

D. Heterogeneity Analysis Added

Subgroup regressionsEstimate models separately by selected groups.

Interaction-based heterogeneityTest whether effects differ across groups.

Period-based analysisCompare effects across different time periods.

Industry heterogeneityCompare effects by industry group.

Country / region heterogeneityCompare effects by country or region categories.

Size-based heterogeneityCompare smaller vs larger entities.

Heterogeneity setup

Grouping variable

Group labels / split rule

E. Standard Error Treatment

Conventional

Use standard model-based errors.

Robust

Request heteroskedasticity-robust inference.

Cluster-robust

Cluster by the entity/panel identifier.

F. Optional Reporting Preference

Significance levels

Results table preference

7

Research Framework

Create one of three common conceptual-framework diagrams using the variables already entered.

Framework type

Diagram labels

Include control variables

8

Generated Research Workflow

Copy the prompt you need. The site does not fabricate results and does not analyse your dataset.

Complete the form and select “Generate Research Workflow”.

Methodological safeguard: generated prompts tell the AI to verify assumptions, use the selected software, avoid inventing values, and ask for actual output before interpreting empirical results.

i

About Version 1

A lightweight MVP focused on prompt generation and framework diagrams.

Google login setup: the page includes a ready hook for Firebase Authentication, but you must paste your own Firebase web-app configuration into the script before Google sign-in can work on your deployed domain. Until then, the button clearly shows that authentication is not configured.

Build research prompts, not another statistical package.