Format Export Email address Password Username Remember me? Recipient's Email Address Your Email Your Name Subject Message Send Me A Copy Name Description Select a length Embed code

Books

Previous Chapter Chapter 71: Partial Correlation Next Chapter

Luiz Moutinho

In: The SAGE Dictionary of Quantitative Management Research

Chapter 71: Partial Correlation

Edited by: Luiz Moutinho & Graeme Hutcheson

DOI: http://dx.doi.org/10.4135/9781446251119.n71

Subject: Quantitative Techniques for Business & Management Research

Find in this title

Citations
Add to My List
Share
Text Size

Citations

Format:

Moutinho, L. (2011). Partial correlation. In L. Moutinho & G. Hutcheson (Eds.), The SAGE dictionary of quantitative management research (pp. 238-239). London: SAGE Publications Ltd doi: 10.4135/9781446251119.n71

Moutinho, Luiz. "Partial Correlation." In The SAGE Dictionary of Quantitative Management Research, edited by Luiz Moutinho and Graeme Hutcheson, 238-239. London: SAGE Publications Ltd, 2011. doi: 10.4135/9781446251119.n71.

Moutinho, L 2011, 'Partial correlation', in Moutinho, L & Hutcheson, G (eds), The sage dictionary of quantitative management research, SAGE Publications Ltd, London, pp. 238-239, viewed 9 December 2019, doi: 10.4135/9781446251119.n71.

Moutinho, Luiz. "Partial Correlation." The SAGE Dictionary of Quantitative Management Research. Eds. Luiz Moutinho and Graeme Hutcheson. London: SAGE Publications Ltd, 2011. 238-239. SAGE Knowledge. Web. 9 Dec. 2019, doi: 10.4135/9781446251119.n71.

Copy to Clipboard

Export:

Have you created a personal profile? Login or create a profile so that you can create alerts and save clips, playlists, and searches.

Email

Please log in from an authenticated institution or log into your member profile to access the email feature.

Whereas the product moment or simple correlation is a measure of association describing the linear association between two variables, a partial correlation coefficient measures the association between two variables after controlling for or adjusting for the effects of one or more additional variables. This statistic is used to answer the following questions:

1.
How strongly are sales related to advertising expenditures when the effect of price is controlled?
2.
Is there an association between market share and size of the sales force after adjusting for the effect of sales promotion?
3.
Are consumers’ perceptions of quality related to their perceptions of prices when the effect of brand image is controlled?

Key Features

Suppose one wanted to calculate the association between X and Y after controlling for a third ...

Looks like you do not have access to this content.

Don’t know how to login?

Click here for free trial login.

Citations
Add to My List
Share
Text Size

Citations

Format:

Copy to Clipboard

Export:

Have you created a personal profile? Login or create a profile so that you can create alerts and save clips, playlists, and searches.

Email

Please log in from an authenticated institution or log into your member profile to access the email feature.

1: Introduction
2: A/B Split Testing
3: Analytic Hierarchy Process
4: Association and Causation in Quantitative Research
5: Association Rule Mining
6: Bass Model
7: Canonical Correlation
8: Chaos Theory
9: Classification and Ranking Belief Simplex
10: Clustering Algorithms
11: Cluster Analysis
12: Coding Conventions for Representing Information
13: Conceptual Equivalence
14: Confidence Intervals
15: Conjoint Analysis
16: Construct Operationalization Review (CORE)
17: Correlation Analysis
18: Correspondence Analysis
19: Cross-National/Cultural Comparisons
20: Cross-Sectional Designs
21: Data Envelopment Analysis in Management: Theory, Methods and Applications
22: Data Mining
23: Data Set Structure
24: Data Transformation
25: Dempster-Shafer Theory
26: Designing Experiments
27: Discriminant Analysis
28: Dominance Analysis
29: DS/AHP
30: Dummy Variable Coding
31: Event Studies Methodology
32: Evaluation Research
33: Experimental Design
34: Exploratory or Confirmatory Factor Analysis
35: Factor Analysis
36: Fuzzy Decision Trees
37: Fuzzy Sets
38: Fuzzy Time Series Models
39: Generalized Linear Mixed Models
40: Generalized Linear Models
41: Geodemographics
42: Geographical Information Systems
43: Growth Models
44: Intraclass Correlation Coefficient
45: Internal and External Validity
46: Item Response Theory
47: Item Response Theory for Management
48: Latent Segments Analysis
49: Latent Variable Models
50: Logical Discriminant Models
51: Logistic Growth Model
52: Logistic Regression
53: Logistic Spline Model
54: Measurement Reliability
55: Measurement Invariance in Multigroup Research
56: Measurement Scales
57: Moderator–Mediator Variable Distinction
58: Mixture Models
59: Multi-Attribute Utility/Value Theory
60: Multidimensional Scaling
61: Multilevel Models
62: Multi-Logistic Growth Model
63: Multinomial Logistic Regression
64: Multi-State Modelling
65: Non-Parametric Measures of Association
66: Optimal Control Models in Management
67: Ordinary Least-Squares Regression
68: Panel Design
69: Paper Versus Electronic Surveys
70: Parametric Tests
71: Partial Correlation
72: Principal Components Analysis
73: Programme Evaluation
74: PROMETHEE Method of Ranking Alternatives
75: Proportional Odds Model
76: Quantile Estimators
77: Quantile Estimators – Bootstrap Confidence Intervals
78: Rasch Model for Measurement
79: Receiver Operating Characteristic
80: Response Styles in Cross-National Research
81: Retail Site Selection
82: Sampling Equivalence in Cross-National Research
83: Sample Size for Proportions
84: Sample Sizes Versus Usable Observations
85: Self-Organizing Maps
86: Single-Case Research Designs
87: Single-Case Single-Baseline Designs
88: Single-Case Multiple-Baseline Designs
89: Simulation – Discrete Event
90: Simulation – Methodology
91: Structural Equation Modelling in Business Management
92: Structural Equation Modelling in Marketing – Part 1: Introduction and Basic Concepts
93: Structural Equation Modelling in Marketing – Part 2: Model Calibration
94: Structural Equation Modelling in Marketing – Part 3: An Example
95: Study Design
96: Survey Design
97: Tabu Search
98: Testing a Sample Hypothesis
99: Validity
100: Variable Precision Rough Sets
101: Voronoi Diagrams
102: Web Surveys

View all chapters View fewer chapters

Keywords

partial correlation,
correlation,
cereals,
measures of association,
control variable,
measures of association/correlation coefficient,
residence

Also from SAGE Publishing

CQ Library American political resources opens in new tab
Data Planet A universe of data opens in new tab
Lean Library Increase the visibility of your library opens in new tab
SAGE Journals World-class research journals opens in new tab
SAGE Research Methods The ultimate methods library opens in new tab
SAGE Stats Data on demand opens in new tab

Browse by Subject

Browse by Content Type

Previous Chapter Chapter 71: Partial Correlation Next Chapter

Looks like you do not have access to this content.

Chapters

Similar content on SAGE Knowledge

Keywords

Also from SAGE Publishing

Previous Chapter Chapter 71: Partial Correlation Next Chapter

Citations

Email

Font Size

Looks like you do not have access to this content.

Citations

Email

Font Size

Chapters

Similar content on SAGE Knowledge

Keywords

Also from SAGE Publishing