On the usefulness of the ICC(1) and R WG index to justify aggregation decisions

Torsten Biemann; Heike Heidemeier

On the usefulness of the ICC(1) and R _WG index to justify aggregation decisions

Torsten Biemann^*, Heike Heidemeier

^*Corresponding author for this work

Research output: Contribution to conference › Oral presentation at a conference

3 Citations (Scopus)

Abstract

In multilevel analyses, the aggregation of lower-level data to a higher level is commonly justified via rWG and ICC(1) indices. In this article, the authors analyze the relationship between these two measures theoretically and by means of Monte Carlo simulations. Simulation results show that only ICC(1) affects decision quality in terms of statistical power, whereas the height of the mean rWG does not impact power estimates. The authors discuss ambiguous settings in which common interpretation of rWG and ICC(1) values are inconsistent and suggest that researchers interested in analyzing the adequacy of aggregating data to a higher level should primarily employ the ICC(1) and only use the rWG as an additional source of information.

Original language	English
Publication status	Published - 2010
Externally published	Yes
Event	70th Annual Meeting of the Academy of Management - Dare to Care: Passion and Compassion in Management Practice and Research, AOM 2010 - Montreal, QC, Canada Duration: 06 Aug 2010 → 10 Aug 2010

Conference

Conference	70th Annual Meeting of the Academy of Management - Dare to Care: Passion and Compassion in Management Practice and Research, AOM 2010
Country/Territory	Canada
City	Montreal, QC
Period	06.08.2010 → 10.08.2010

Keywords

Data aggregation
Multilevel
RWG

ASJC Scopus subject areas

Management of Technology and Innovation
Industrial Relations

Cite this

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title = "On the usefulness of the ICC(1) and R WG index to justify aggregation decisions",

abstract = "In multilevel analyses, the aggregation of lower-level data to a higher level is commonly justified via rWG and ICC(1) indices. In this article, the authors analyze the relationship between these two measures theoretically and by means of Monte Carlo simulations. Simulation results show that only ICC(1) affects decision quality in terms of statistical power, whereas the height of the mean rWG does not impact power estimates. The authors discuss ambiguous settings in which common interpretation of rWG and ICC(1) values are inconsistent and suggest that researchers interested in analyzing the adequacy of aggregating data to a higher level should primarily employ the ICC(1) and only use the rWG as an additional source of information.",

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author = "Torsten Biemann and Heike Heidemeier",

year = "2010",

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On the usefulness of the ICC(1) and R _WG index to justify aggregation decisions. / Biemann, Torsten; Heidemeier, Heike.
2010. Paper presented at 70th Annual Meeting of the Academy of Management - Dare to Care: Passion and Compassion in Management Practice and Research, AOM 2010, Montreal, QC, Canada.

Research output: Contribution to conference › Oral presentation at a conference

TY - CONF

T1 - On the usefulness of the ICC(1) and R WG index to justify aggregation decisions

AU - Biemann, Torsten

AU - Heidemeier, Heike

PY - 2010

Y1 - 2010

N2 - In multilevel analyses, the aggregation of lower-level data to a higher level is commonly justified via rWG and ICC(1) indices. In this article, the authors analyze the relationship between these two measures theoretically and by means of Monte Carlo simulations. Simulation results show that only ICC(1) affects decision quality in terms of statistical power, whereas the height of the mean rWG does not impact power estimates. The authors discuss ambiguous settings in which common interpretation of rWG and ICC(1) values are inconsistent and suggest that researchers interested in analyzing the adequacy of aggregating data to a higher level should primarily employ the ICC(1) and only use the rWG as an additional source of information.

AB - In multilevel analyses, the aggregation of lower-level data to a higher level is commonly justified via rWG and ICC(1) indices. In this article, the authors analyze the relationship between these two measures theoretically and by means of Monte Carlo simulations. Simulation results show that only ICC(1) affects decision quality in terms of statistical power, whereas the height of the mean rWG does not impact power estimates. The authors discuss ambiguous settings in which common interpretation of rWG and ICC(1) values are inconsistent and suggest that researchers interested in analyzing the adequacy of aggregating data to a higher level should primarily employ the ICC(1) and only use the rWG as an additional source of information.

KW - Data aggregation

KW - Multilevel

KW - RWG

UR - http://www.scopus.com/inward/record.url?scp=84858654344&partnerID=8YFLogxK

M3 - Oral presentation at a conference

AN - SCOPUS:84858654344

T2 - 70th Annual Meeting of the Academy of Management - Dare to Care: Passion and Compassion in Management Practice and Research, AOM 2010

Y2 - 6 August 2010 through 10 August 2010

ER -