語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Does Taking a More Holistic View of ...
~
Yost, Allison Brown.
FindBook
Google Book
Amazon
博客來
Does Taking a More Holistic View of Personality Improve its Predictive Utility? A Comparison Multiple Regression, Fuzzy Cluster Analysis, and Indirect Mixture Modeling for Predicting Leadership Effectiveness.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Does Taking a More Holistic View of Personality Improve its Predictive Utility? A Comparison Multiple Regression, Fuzzy Cluster Analysis, and Indirect Mixture Modeling for Predicting Leadership Effectiveness./
作者:
Yost, Allison Brown.
面頁冊數:
222 p.
附註:
Source: Dissertation Abstracts International, Volume: 75-07(E), Section: B.
Contained By:
Dissertation Abstracts International75-07B(E).
標題:
Psychology, Psychometrics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3615722
ISBN:
9781303817991
Does Taking a More Holistic View of Personality Improve its Predictive Utility? A Comparison Multiple Regression, Fuzzy Cluster Analysis, and Indirect Mixture Modeling for Predicting Leadership Effectiveness.
Yost, Allison Brown.
Does Taking a More Holistic View of Personality Improve its Predictive Utility? A Comparison Multiple Regression, Fuzzy Cluster Analysis, and Indirect Mixture Modeling for Predicting Leadership Effectiveness.
- 222 p.
Source: Dissertation Abstracts International, Volume: 75-07(E), Section: B.
Thesis (Ph.D.)--The George Washington University, 2014.
When using personality to predict leadership outcomes, researchers typically use either bivariate correlations or additive, linear multiple regression models. Recently, however, some researchers have suggested that the relationship between personality and leadership may be more complex than typically represented in the literature. The purpose of the current study was to evaluate the predictive utility of two under-utilized statistical modeling techniques that take a holistic approach to modeling the personality-leadership relationship -- fuzzy cluster analysis and indirect mixture modeling. These statistical techniques were applied to an archival data set containing personality and leadership effectiveness information for 619 department managers at a grocery chain in the United States. Using this data, four statistical models were tested and compared in terms of their overall fit, predictive validity, and generalizability: (1) a traditional main-effects only multiple regression model, (2) a regression model that includes theoretically relevant interactions and nonlinear effects, (3) fuzzy cluster analysis, and (4) indirect mixture modeling. Results indicated that although indirect mixture modeling outperformed both multiple regression and fuzzy cluster analysis across all four leadership criteria in the development sample, this technique experienced the most shrinkage in the validation sample. In contrast, the main-effects multiple regression models explained a small, but significant amount of variance in the leadership effectiveness outcomes, the magnitudes of which were stable across samples.
ISBN: 9781303817991Subjects--Topical Terms:
1017742
Psychology, Psychometrics.
Does Taking a More Holistic View of Personality Improve its Predictive Utility? A Comparison Multiple Regression, Fuzzy Cluster Analysis, and Indirect Mixture Modeling for Predicting Leadership Effectiveness.
LDR
:02659nam a2200289 4500
001
1962890
005
20140829084625.5
008
150210s2014 ||||||||||||||||| ||eng d
020
$a
9781303817991
035
$a
(MiAaPQ)AAI3615722
035
$a
AAI3615722
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Yost, Allison Brown.
$3
2099022
245
1 0
$a
Does Taking a More Holistic View of Personality Improve its Predictive Utility? A Comparison Multiple Regression, Fuzzy Cluster Analysis, and Indirect Mixture Modeling for Predicting Leadership Effectiveness.
300
$a
222 p.
500
$a
Source: Dissertation Abstracts International, Volume: 75-07(E), Section: B.
500
$a
Adviser: David P. Costanza.
502
$a
Thesis (Ph.D.)--The George Washington University, 2014.
520
$a
When using personality to predict leadership outcomes, researchers typically use either bivariate correlations or additive, linear multiple regression models. Recently, however, some researchers have suggested that the relationship between personality and leadership may be more complex than typically represented in the literature. The purpose of the current study was to evaluate the predictive utility of two under-utilized statistical modeling techniques that take a holistic approach to modeling the personality-leadership relationship -- fuzzy cluster analysis and indirect mixture modeling. These statistical techniques were applied to an archival data set containing personality and leadership effectiveness information for 619 department managers at a grocery chain in the United States. Using this data, four statistical models were tested and compared in terms of their overall fit, predictive validity, and generalizability: (1) a traditional main-effects only multiple regression model, (2) a regression model that includes theoretically relevant interactions and nonlinear effects, (3) fuzzy cluster analysis, and (4) indirect mixture modeling. Results indicated that although indirect mixture modeling outperformed both multiple regression and fuzzy cluster analysis across all four leadership criteria in the development sample, this technique experienced the most shrinkage in the validation sample. In contrast, the main-effects multiple regression models explained a small, but significant amount of variance in the leadership effectiveness outcomes, the magnitudes of which were stable across samples.
590
$a
School code: 0075.
650
4
$a
Psychology, Psychometrics.
$3
1017742
650
4
$a
Psychology, Personality.
$3
1017585
650
4
$a
Psychology, Industrial.
$3
520063
690
$a
0632
690
$a
0625
690
$a
0624
710
2
$a
The George Washington University.
$b
Organizational Sciences and Communication.
$3
2099023
773
0
$t
Dissertation Abstracts International
$g
75-07B(E).
790
$a
0075
791
$a
Ph.D.
792
$a
2014
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3615722
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9257888
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入