Multilevel analyses in marketing research: differentiating analytical outcomes

Jan Wieske, Nick J. Lee, Amanda J. Broderick, Jeremy F. Dawson, Rolf van Dick

Research output: Contribution to journalArticle

Abstract

Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.
Original languageEnglish
Pages (from-to)321-340
Number of pages20
JournalJournal of Marketing Theory and Practice
Volume16
Issue number4
DOIs
Publication statusPublished - Sep 2008

Fingerprint

Marketing
Marketing research
Data structures
Hierarchical linear modeling
Effect size
Monte Carlo simulation
Grouped data

Keywords

  • research
  • marketing
  • analytical outcomes

Cite this

Wieske, Jan ; Lee, Nick J. ; Broderick, Amanda J. ; Dawson, Jeremy F. ; van Dick, Rolf. / Multilevel analyses in marketing research : differentiating analytical outcomes. In: Journal of Marketing Theory and Practice. 2008 ; Vol. 16, No. 4. pp. 321-340.
@article{586159098eb84abca58d693b84c81e0d,
title = "Multilevel analyses in marketing research: differentiating analytical outcomes",
abstract = "Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.",
keywords = "research, marketing, analytical outcomes",
author = "Jan Wieske and Lee, {Nick J.} and Broderick, {Amanda J.} and Dawson, {Jeremy F.} and {van Dick}, Rolf",
year = "2008",
month = "9",
doi = "10.2753/MTP1069-6679160405",
language = "English",
volume = "16",
pages = "321--340",
journal = "Journal of Marketing Theory and Practice",
issn = "1069-6679",
publisher = "M.E. Sharpe Inc.",
number = "4",

}

Multilevel analyses in marketing research : differentiating analytical outcomes. / Wieske, Jan; Lee, Nick J.; Broderick, Amanda J.; Dawson, Jeremy F.; van Dick, Rolf.

In: Journal of Marketing Theory and Practice, Vol. 16, No. 4, 09.2008, p. 321-340.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Multilevel analyses in marketing research

T2 - differentiating analytical outcomes

AU - Wieske, Jan

AU - Lee, Nick J.

AU - Broderick, Amanda J.

AU - Dawson, Jeremy F.

AU - van Dick, Rolf

PY - 2008/9

Y1 - 2008/9

N2 - Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.

AB - Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.

KW - research

KW - marketing

KW - analytical outcomes

UR - http://www.scopus.com/inward/record.url?scp=52749098360&partnerID=8YFLogxK

UR - https://www.tandfonline.com/doi/abs/10.2753/MTP1069-6679160405

U2 - 10.2753/MTP1069-6679160405

DO - 10.2753/MTP1069-6679160405

M3 - Article

VL - 16

SP - 321

EP - 340

JO - Journal of Marketing Theory and Practice

JF - Journal of Marketing Theory and Practice

SN - 1069-6679

IS - 4

ER -