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Dataset Comparison

Last updated: Jun 3, 2026, 8:09 AM EDT

This page provides a comprehensive side-by-side comparison of all four primary result groups. Each group represents an independent dataset with progressively less restrictive quality criteria. Researchers can use this comparison to assess how data cleaning decisions affect statistical conclusions.

Sample Overview

#Result GroupNDefinition
1Conservative Clean140Prolific APPROVED + all quality checks (IRI, duration >= 540s, reCAPTCHA, straightlining, auth)
2Flexible Clean231Prolific APPROVED + basic quality (all 3 IRIs + duration >= 480s)
3Prolific Accepted440All deduplicated V2 rows with Prolific APPROVED status
4All V2 Finished689Finished + duration >= 120s (extreme speeders excluded)

Core Metrics Comparison

All descriptive statistics, reliability coefficients, and correlations are shown for each result group. The Δ column shows the difference from Conservative Clean (the strictest dataset). Deltas > 0.05 are highlighted in amber.

MetricConservative CleanFlexible CleanProlific AcceptedAll V2 FinishedΔ FlexibleΔ ProlificΔ All
Barrier Grand Mean2.85662.88042.88672.8956+0.0238+0.0301+0.0390
Barrier SD0.66410.71990.72670.7849+0.0558+0.0626+0.1208
Readiness Grand Mean3.04683.05463.09303.2065+0.0078+0.0462+0.1597
Readiness SD0.59780.66310.65600.7191+0.0653+0.0582+0.1213
Maturity Grand Mean3.05583.04953.11353.2261-0.0063+0.0577+0.1703
Maturity SD0.70690.81040.79340.8112+0.1035+0.0865+0.1043
B-R Correlation-0.4083-0.4330-0.3299-0.2654-0.0247+0.0784+0.1429
B-M Correlation-0.1890-0.2872-0.2472-0.2349-0.0982-0.0582-0.0459
R-M Correlation0.60010.70660.71970.7254+0.1065+0.1196+0.1253
Alpha Barriers0.86640.88590.88970.9086+0.0195+0.0233+0.0422
Alpha Readiness0.87200.91230.91280.9273+0.0403+0.0408+0.0553
Alpha Maturity0.82640.88640.88550.8927+0.0600+0.0591+0.0663

Survey Demographics Comparison (Qualtrics)

Role distribution and organization size breakdown for each result group, based on self-reported survey responses (Q1, Q4). These are organizational demographics from the TABS instrument. Prolific platform demographics (age, sex, ethnicity, plus prescreener fields like industry, company size, and occupation) are collected separately and can be used to cross-validate these survey responses via Prolific Participant ID.

Tech vs Non-Tech Composition

Result GroupNTechnicalNon-TechnicalOther% Tech
Conservative Clean14028112020.0%
Flexible Clean23152179022.5%
Prolific Accepted44098342022.3%
All V2 Finished689174515025.3%

Organization Size Distribution

Result Group<100100-499500-9991000-49995000-999910000+
Conservative Clean214913301116
Flexible Clean337732481427
Prolific Accepted7313363843651
All V2 Finished1062081091295582

Filter Bias Analysis

This analysis tests whether stricter quality filters disproportionately exclude certain demographics. A Chi-square test for independence is computed across the four result groups for role, organization size, and profit model.

Demographic CategoryChi-Square (χ²)dfp-valueInterpretation
Role (Tech vs Non-Tech)2.6330.4524No significant difference (demographics stable)
Organization Size7.22150.9513No significant difference (demographics stable)
Profit Model3.4960.7454No significant difference (demographics stable)

Profit Model Distribution

Result GroupFor-ProfitNon-ProfitGovernment/Public Sector
Conservative Clean992120
Flexible Clean1604031
Prolific Accepted3137948
All V2 Finished50510777

Effect Size Comparison

Cohen’s d effect sizes for key group comparisons across all four result groups. This shows how effect sizes shift as the sample becomes less restrictive.

Tech vs Non-Tech (Cohen’s d)

ConstructConservative CleanFlexible CleanProlific AcceptedAll V2 Finished
barriers-0.133-0.228-0.045-0.084
readiness0.6590.7290.6540.526
maturity0.3130.4320.4120.400

Large vs Small/Medium Org (Cohen’s d)

ConstructConservative CleanFlexible CleanProlific AcceptedAll V2 Finished
barriers0.3430.2740.0640.053
readiness-0.074-0.1240.0210.016

Interpretation Guide

Metrics that remain stable across all four groups suggest robust findings that are not sensitive to data cleaning decisions. Metrics that show large deltas (highlighted in amber) between Conservative Clean and less restrictive groups warrant further investigation, as the finding may depend on sample composition.

As a rule of thumb: if a Cohen’s d shifts by more than 0.1 between Conservative Clean and All V2 Finished, the effect size may be inflated or attenuated by lower-quality responses. Similarly, if Cronbach’s α drops below 0.70 in larger samples, it may indicate that less-engaged respondents are adding noise to the scale.

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