Multilevel measurement models for group collective constructs

Joseph A Bonito, Joann Keyton

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

When studying groups and teams, researchers can include individual-level and/or group-level phenomena in their research design. Distinguishing between individualand group-level constructs is necessary before choosing statistical analysis and interpretation. This article addresses multilevel measurement models for data collected from individuals within small discussion groups. Measurement models for this class of variables present several challenges because the data are nonindependent. We propose a conceptual framework for establishing a set of models a priori based on the notion of collective constructs and describe means for testing structures at both levels of analysis. Using two data sets, we discuss the conceptual and statistical problems associated with developing measurement models for group data collected at the individual level.

Original languageEnglish (US)
Pages (from-to)1-21
Number of pages21
JournalGroup Dynamics
Volume23
Issue number1
DOIs
StatePublished - Mar 1 2019

Fingerprint

Research Design
Research Personnel
Datasets

Keywords

  • Collective constructs
  • Latent measurement models
  • Multilevel models
  • Nonindependence

ASJC Scopus subject areas

  • Social Psychology
  • Applied Psychology

Cite this

Multilevel measurement models for group collective constructs. / Bonito, Joseph A; Keyton, Joann.

In: Group Dynamics, Vol. 23, No. 1, 01.03.2019, p. 1-21.

Research output: Contribution to journalArticle

@article{dc001057b8dd4d5e934063f9b06b9e4e,
title = "Multilevel measurement models for group collective constructs",
abstract = "When studying groups and teams, researchers can include individual-level and/or group-level phenomena in their research design. Distinguishing between individualand group-level constructs is necessary before choosing statistical analysis and interpretation. This article addresses multilevel measurement models for data collected from individuals within small discussion groups. Measurement models for this class of variables present several challenges because the data are nonindependent. We propose a conceptual framework for establishing a set of models a priori based on the notion of collective constructs and describe means for testing structures at both levels of analysis. Using two data sets, we discuss the conceptual and statistical problems associated with developing measurement models for group data collected at the individual level.",
keywords = "Collective constructs, Latent measurement models, Multilevel models, Nonindependence",
author = "Bonito, {Joseph A} and Joann Keyton",
year = "2019",
month = "3",
day = "1",
doi = "10.1037/gdn0000096",
language = "English (US)",
volume = "23",
pages = "1--21",
journal = "Group Dynamics",
issn = "1089-2699",
publisher = "American Psychological Association",
number = "1",

}

TY - JOUR

T1 - Multilevel measurement models for group collective constructs

AU - Bonito, Joseph A

AU - Keyton, Joann

PY - 2019/3/1

Y1 - 2019/3/1

N2 - When studying groups and teams, researchers can include individual-level and/or group-level phenomena in their research design. Distinguishing between individualand group-level constructs is necessary before choosing statistical analysis and interpretation. This article addresses multilevel measurement models for data collected from individuals within small discussion groups. Measurement models for this class of variables present several challenges because the data are nonindependent. We propose a conceptual framework for establishing a set of models a priori based on the notion of collective constructs and describe means for testing structures at both levels of analysis. Using two data sets, we discuss the conceptual and statistical problems associated with developing measurement models for group data collected at the individual level.

AB - When studying groups and teams, researchers can include individual-level and/or group-level phenomena in their research design. Distinguishing between individualand group-level constructs is necessary before choosing statistical analysis and interpretation. This article addresses multilevel measurement models for data collected from individuals within small discussion groups. Measurement models for this class of variables present several challenges because the data are nonindependent. We propose a conceptual framework for establishing a set of models a priori based on the notion of collective constructs and describe means for testing structures at both levels of analysis. Using two data sets, we discuss the conceptual and statistical problems associated with developing measurement models for group data collected at the individual level.

KW - Collective constructs

KW - Latent measurement models

KW - Multilevel models

KW - Nonindependence

UR - http://www.scopus.com/inward/record.url?scp=85062797578&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85062797578&partnerID=8YFLogxK

U2 - 10.1037/gdn0000096

DO - 10.1037/gdn0000096

M3 - Article

AN - SCOPUS:85062797578

VL - 23

SP - 1

EP - 21

JO - Group Dynamics

JF - Group Dynamics

SN - 1089-2699

IS - 1

ER -