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Data Quality

Why Many Research Instruments Lack Face Validity—And How to Fix It

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Why Many Research Instruments Fail Face Validity

Face validity is the most intuitive—and often the most ignored—dimension of measurement quality. If respondents cannot immediately understand what a question measures, the resulting data become fragile, regardless of high Cronbach’s alpha, AVE, or composite reliability. Poor face validity leads to misinterpretation, satisficing, social desirability distortions, and ultimately flawed statistical conclusions. In reality, many survey … Read more

Why Translated Instruments Fail Without Localization

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Why-translated-instruments-fail-without-localization

Understanding the Problem: Translation Isn’t Enough In global research, translation is often mistaken for localization. Many researchers assume that once a questionnaire or scale is linguistically translated, it becomes universally applicable.However, translation alone rarely guarantees conceptual equivalence—the idea that a question measures the same construct in another language or culture. For example, a “satisfaction survey” … Read more

Why Data from Developing Countries Must Include Informal Economy

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Why-data-from-developing-countries-must-include-informal-economy

In development research, we often analyze statistical models, national accounts, surveys, and international data repositories. Yet one critical factor frequently slips through the cracks: the informal economy — the unregistered, unregulated, and largely unrecorded portion of production and employment. Failing to recognize this hidden sector distorts our understanding of how economies function, especially in the … Read more

Dirty Data Leads to Wrong Results

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Dirty-Data - leads-to-wrong-results

In research, complex models and advanced statistical techniques often get the spotlight. But here’s the truth: if data is dirty, results are wrong—no matter how advanced the analysis looks. Data cleaning is not optional. It is the backbone of research integrity, transforming raw inputs into credible evidence. Neglecting it risks misleading findings, wasted resources, and … Read more