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Joško Sindik1

1Institute for Anthropological Research, Zagreb, Croatia

Two Aspects of Bias in Multivariate Studies: Mixing Specific with General Concepts and “Comparing Apples and Oranges”

Dvije vrste pristrasnosti u multivarijatnim studijama: „Pristrasnost pomiješanih nivoa“ i „Pristrasnost pomiješanih konstrukata“

Monten. J. Sports Sci. Med. 2014, 3(1), 23-29


This paper presents two types of bias that occur relatively often when using multivariate analysis. For both types of bias, it is characteristic that the number and choice of different types of variables are not balanced by application of clear methodological rules. Following the interpretation of broader theoretical positions, which include "confirmation bias" ( of initial hypothesis) and "mis¬specification bias", a description of two types of bias characteristic of multivariate analysis are given: "mixed-level bias" (in terms of specificity - generality) and "mixed-constructs bias" . Both types of bias further enhance the disparity in the number and ratio of different types of variables in the same multivariate analysis. Details of situations, when these two types of bias appear, are presented and displayed in four different examples. Several strategies are proposed as to how these types of bias can try to be avoided, during the preparation of studies, during the statistical analyses and their interpretation.


Mixed-constructs bias, Mixed-level bias, Multivariate analysis

Abstract (MNE)

U članku su predstavljene dvije vrste pristrasnosti koje razmjerno često nastaju pri korišćenju multivarijatnih analiza. Za obije vrste pristrasnosti, karakteristično je da broj i odabir različitih tipova varijabli nisu uravnoteženi primjenom jasnih metodoloških pravila. Nakon tumačenja širih teorijskih polazišta, koja obuhvataju “pristrasnost potvrđivanja” (inicijalnih hipoteza) i “pristrasnost nedostatka specifikacije”, dat je opis dvije vrste pristrasnosti karakterističnih za multivarijatne analize: “pristrasnost pomiješanih nivoa”(specifičnosti-uopštenost), te “pristrasnost pomiješanih konstrukata”. Obije vrste pristrasnosti dodatno pojačava nesraz¬mjer¬nost u broju i omjeru različitih tipova varijabli u istoj multivarijatnoj analizi. Pojedinosti o situacijama pojavljivanja dvije pred¬stav¬ljene vrste pristrasnosti su prikazane na četiri različita primjera. Predložene su strategije kako se navedene vrste pristranosti mogu po¬kušati izbjeći, tokom pripreme istraživanja, ali i tokom statističkih analiza i njihove interpretacije.

Keywords (MNE)

pristrasnost pomiješanih konstrukata, pristrasnost pomiješanih nivoa, multivarijatna analiza

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