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Dataset Comparison

Last updated: Sep 1, 2026, 6:35 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 Clean158Prolific APPROVED + all quality checks (IRI, duration >= 540s, reCAPTCHA, straightlining, auth)
2Flexible Clean257Prolific APPROVED + basic quality (all 3 IRIs + duration >= 480s)
3Prolific Accepted481All deduplicated V2 rows with Prolific APPROVED status
4All V2 Finished767Finished + 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 Mean2.86852.88372.88662.8881+0.0152+0.0181+0.0196
Barrier SD0.66600.72070.71950.7810+0.0547+0.0535+0.1150
Readiness Grand Mean3.03973.06603.09763.2037+0.0263+0.0579+0.1640
Readiness SD0.59330.66170.65180.7239+0.0684+0.0585+0.1306
Maturity Grand Mean3.06763.06493.11943.2251-0.0027+0.0518+0.1575
Maturity SD0.70520.81430.78900.8123+0.1091+0.0838+0.1071
B-R Correlation-0.3998-0.4238-0.3190-0.2540-0.0240+0.0808+0.1458
B-M Correlation-0.1656-0.2677-0.2317-0.2233-0.1021-0.0661-0.0577
R-M Correlation0.56880.69270.71380.7190+0.1239+0.1450+0.1502
Alpha Barriers0.86560.88300.88490.9070+0.0174+0.0193+0.0414
Alpha Readiness0.86830.90730.90860.9266+0.0390+0.0403+0.0583
Alpha Maturity0.81960.88380.87910.8899+0.0642+0.0595+0.0703

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 Clean15830128019.0%
Flexible Clean25758199022.6%
Prolific Accepted481106375022.0%
All V2 Finished767187580024.4%

Organization Size Distribution

Result Group<100100-499500-9991000-49995000-999910000+
Conservative Clean295216311119
Flexible Clean448236491432
Prolific Accepted8614270864057
All V2 Finished1312241201386193

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)2.5430.4681No significant difference (demographics stable)
Organization Size6.44150.9714No significant difference (demographics stable)
Profit Model3.0260.8063No significant difference (demographics stable)

Profit Model Distribution

Result GroupFor-ProfitNon-ProfitGovernment/Public Sector
Conservative Clean1122323
Flexible Clean1814234
Prolific Accepted3458254
All V2 Finished56411885

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-0.082-0.153-0.021-0.062
readiness0.5040.5830.5870.489
maturity0.1730.3020.3490.360

Large vs Small/Medium Org (Cohen’s d)

ConstructConservative CleanFlexible CleanProlific AcceptedAll V2 Finished
barriers0.4130.3070.0620.010
readiness-0.226-0.136-0.0080.049

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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