6533b7d5fe1ef96bd1263e03

RESEARCH PRODUCT

Automatic regrouping of strata in the goodness-of-fit chi-square test

Carlos Vidal-meliáJuan Manuel Pérez-salamero GonzálezManuel Ventura-marcoMarta Regúlez-castilloVicente A. Núñez Antón

subject

Contingency tableComputer scienceContinuous Sample of Working Lives62G10 62P25MathematicaSample (statistics):62 Statistics::62P Applications [Classificació AMS]Visual Basic for ApplicationsEconomiaTest (assessment):62 Statistics::62G Nonparametric inference [Classificació AMS]Goodness of fitFinancesSample size determination:Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC]StatisticsVisual Basic for ApplicationsChi-square testGoodness-of-fit chi-square test statistical software Visual Basic for Applications Mathematica Continuous Sample of Working Livesstatistical softwareGoodness-of-fit chi-square testEconometríaCategorical variable

description

Pearson’s chi-square test is widely employed in social and health sciences to analyze categorical data and contingency tables. For the test to be valid, the sample size must be large enough to provide a minimum number of expected elements per category. This paper develops functions for regrouping strata automatically no matter where they are located, thus enabling the goodness-of-fit test to be performed within an iterative procedure. The functions are written in Excel VBA (Visual Basic for Applications) and in Mathematica. The usefulness and performance of these functions is illustrated by means of a simulation study and the application to different datasets. Finally, the iterative use of the functions is applied to the Continuous Sample of Working Lives, a dataset that has been used in a considerable number of studies, especially on labor economics and the Spanish public pension system.

yearjournalcountryeditionlanguage
2019-06-11
http://hdl.handle.net/20.500.11797/RP3411