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A	
  Presenta*on	
  from	
  The	
  NewMR	
  “Advances	
  in	
  
Quan*ta*ve	
  Research”	
  Event	
  
19	
  September,	
  2012	
  
Event	
  sponsored	
  by	
  Affinnova	
  
All	
  copyright	
  owned	
  by	
  The	
  Future	
  Place	
  and	
  the	
  presenters	
  of	
  the	
  material	
  
For	
  more	
  informa=on	
  about	
  Affinnova	
  visit	
  www.affinnova.com	
  
For	
  more	
  informa=on	
  about	
  NewMR	
  events	
  visit	
  newmr.org	
  
Common	
  Method	
  Variance	
  –	
  A	
  threat	
  to	
  Quality	
  of	
  
data	
  
	
  
Mavi	
  Glinoga	
  PhD,	
  Monash	
  University 	
   	
  	
  
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Common Method Variance
Mavi Glinoga
PhD in Marketing
Monash University
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Content
1.  What is Common Method Variance?
2.  Sources of Common Method Variance
3.  What to do to alleviate CMV
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
What is Common Method Variance?
“A systematic error variance or amount of spurious covariance
shared amongst variables because of common method used in
collecting data” (Buckley et al 1990; Malhotra et al 2006).
Consequence:
CMV can deflate/inflate the empirical estimates of true
relationships between constructs (Fiske1982)
- lead to inappropriate rejection of theory/hypothesis
- threatens the validity of measures
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Why should we care about CMV?
•  We care about correlation accuracies
•  It is a significant problem that accounts for up to
27% of variation observed in social science
research ( Lindell and Whitney 2001).
•  Identifying the degree of CMV is important because
it declares the validity of observed relationships
(Podsakoff et al 2003; Malhotra, Kim et al 2006).
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Example
Hypothesis: Higher Enjoyment in work
training (eg. NewMR webinar), leads to
Workplace Loyalty
Enjoyment	
  	
  in	
  
work	
  training	
  
Workplace	
  
Loyalty	
  	
  
-­‐	
  0.65	
  
0.55	
  
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Major Sources of CMV?
-  Social desirability (Ganster et al 1983)
-  Ambiguous wording (Hufnagle and Conca 1994)
-  Scale length (Harrison et al 1996)
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Source	
  Categories	
  	
   Explana*on	
   Type	
  of	
  Bias	
  	
  
Common	
  Rater	
  Effects	
  
	
  
Arises	
  when	
  the	
  
ques=onnaire	
  brings	
  forth	
  
changes	
  in	
  the	
  
respondent’s	
  mood	
  and	
  
cogni=ve	
  processing	
  
(Podsakoff	
  et	
  al	
  2003;	
  
Lindell	
  &	
  Whitney	
  2001)	
  	
  
Acquiesence	
  bias	
  
	
  
-­‐ Agreeing	
  to	
  everything	
  
-­‐ Extreme	
  responses	
  	
  
	
  
Item	
  demand	
  
characteris*cs	
  ,	
  	
  
	
  
Item	
  
context	
  effects	
  and	
  
	
  
Measurement	
  context	
  	
  
effects	
  	
  
	
  
-­‐ Context	
  induced	
  mood	
  
-­‐ Social	
  desirability	
  	
  
Response	
  style	
  bias	
  	
  
	
  
-­‐	
  Over-­‐repor@ng	
  socially	
  
desirable	
  behaviours,	
  and	
  
under	
  repor@ng	
  socially	
  
undesirable	
  behaviours	
  	
  
Sources of CMV?
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Measurement Instrument
1.  Check for the sensitivity of Questions
-  Sensitive questions can lead to systematic
misreporting because of social desirability
2. Questionnaire length and order of questions
-  The longer the questionnaire, the more issue of
social desirability (Holtgraves 2004)
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Mode of Administration
1.  Paper
-  Check for visual design effects
-  Limit visual stimulus
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Mode of Administration
2. Online
–  Online – screensize, configuration, compatibility with operation system and
harware used by responsdent (Dillman 2007)
–  Previous research shows that answers to online survey questions are affected by
design choices – eg. ordering of questions (Dillman 2007; Couper et al 2001),
layout (Winter 2002; Christian 2003; Toepel et al 2006)
–  Grouping related items on a single screen is likely to lead respondents to view
the items as related entities. Thus, increasing the correlation among them
(Strack, Schwarz and Wanke 1991; Schwarz and Sudman 1996; Tourangeau et
al 2004; Dillman 2007)
•  Correlations are higher for items that appear together on a screen than
among items separated across several screens (Couper, Traugott and
Lamias 2001; Tourangeau et al 2004; Peytchev et al 2006)
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
How	
  much	
  do	
  you	
  enjoy	
  work	
  training?	
  
Please	
  indicate	
  how	
  much	
  you	
  agree	
  to	
  the	
  following	
  statement	
  on	
  your	
  sense	
  of	
  enjoyment	
  with	
  work	
  training	
  
Completely
disagree	
  
Barely
agree	
  
Slightly
Agree	
  
Moderately
Agree	
  
Agree	
   Highly
Agree	
  
Completely
Agree	
  
I feel energised when I participate in training sessions at work	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
I feel motivated when we have training at work	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
Work training is fun 	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
I feel happy during training activites	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
How	
  do	
  you	
  feel	
  about	
  your	
  workplace?	
  
Please	
  indicate	
  how	
  much	
  you	
  agree	
  to	
  the	
  following	
  statement	
  on	
  how	
  you	
  feel	
  about	
  your	
  workplace	
  
Completely
disagree	
  
Barely
agree	
  
Slightly
Agree	
  
Moderatel
y Agree	
  
Agree	
   Highly
Agree	
  
Completely
Agree	
  
I am committed to my workplace	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
I love the company I work for	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
I always work for the success of the company I work for 	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
I want to stay in this workplace forever 	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
2 scales in one screen – not recommended especially if
constructs are hypothesised to be correlated
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
1 scale – recommended
How	
  much	
  do	
  you	
  enjoy	
  work	
  training?	
  
Please	
  indicate	
  how	
  much	
  you	
  agree	
  to	
  the	
  following	
  statement	
  on	
  your	
  sense	
  of	
  enjoyment	
  with	
  work	
  training	
  
Completely
disagree	
  
Barely
agree	
  
Slightly
Agree	
  
Moderately
Agree	
  
Agree	
   Highly
Agree	
  
Completely
Agree	
  
I feel energised when I participate in training sessions at work	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
I feel motivated when we have training at work	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
Work training is fun 	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
I feel happy during training activites	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
   ¡	
  
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Correlation comparisons
Correla*on	
  Coefficient	
  
2	
  Scales	
  in	
  1	
  screen	
   0.76**	
  
1	
  construct	
  in	
  1	
  screen	
   0.55***	
  
Hypothesis:	
  Higher	
  	
  Enjoyment	
  in	
  work	
  training	
  (eg.	
  NewMR	
  
webinar),	
  	
  leads	
  to	
  Workplace	
  Loyalty	
  	
  	
  
***p	
  <	
  0.001	
  
**	
  p	
  <0.01	
  
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Mode of Administration
3. Telephone interviews
-  Socio-cultural impact of interviewers
-  Mode effect
-  Respondents at home vs somewhere else (mobile respondents)
-  Consider dual-frame methodology
-  Respondent familiarity with interviewers or company
(longitudinal studies)
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Statistically Testing for CMV
-  Harman’s Common Factor
-  Partial correlation procedure
- Marker Variable Technique
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Thank you
Mavi Glinoga
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Q & A
Mavi Glinoga
Monash University
Sue York
NewMR
Mavi Glinoga PhD, Monash University, Australia
NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1
Thank you
Mavi Glinoga
Email: maviglinoga@gmail.com
LinkedIn: Mavi Glinoga
Twitter: @Mavi_Glinoga
A	
  Presenta*on	
  from	
  The	
  NewMR	
  “Advances	
  in	
  
Quan*ta*ve	
  Research”	
  Event	
  
19	
  September,	
  2012	
  
Event	
  sponsored	
  by	
  Affinnova	
  
All	
  copyright	
  owned	
  by	
  The	
  Future	
  Place	
  and	
  the	
  presenters	
  of	
  the	
  material	
  
For	
  more	
  informa=on	
  about	
  Affinnova	
  visit	
  www.affinnova.com	
  
For	
  more	
  informa=on	
  about	
  NewMR	
  events	
  visit	
  newmr.org	
  
Common	
  Method	
  Variance	
  –	
  A	
  threat	
  to	
  Quality	
  of	
  
data	
  
	
  
Mavi	
  Glinoga	
  PhD,	
  Monash	
  University 	
   	
  	
  

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Mavi glinoga advances in quant - 2011

  • 1. A  Presenta*on  from  The  NewMR  “Advances  in   Quan*ta*ve  Research”  Event   19  September,  2012   Event  sponsored  by  Affinnova   All  copyright  owned  by  The  Future  Place  and  the  presenters  of  the  material   For  more  informa=on  about  Affinnova  visit  www.affinnova.com   For  more  informa=on  about  NewMR  events  visit  newmr.org   Common  Method  Variance  –  A  threat  to  Quality  of   data     Mavi  Glinoga  PhD,  Monash  University      
  • 2. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Common Method Variance Mavi Glinoga PhD in Marketing Monash University
  • 3. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Content 1.  What is Common Method Variance? 2.  Sources of Common Method Variance 3.  What to do to alleviate CMV
  • 4. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 What is Common Method Variance? “A systematic error variance or amount of spurious covariance shared amongst variables because of common method used in collecting data” (Buckley et al 1990; Malhotra et al 2006). Consequence: CMV can deflate/inflate the empirical estimates of true relationships between constructs (Fiske1982) - lead to inappropriate rejection of theory/hypothesis - threatens the validity of measures
  • 5. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Why should we care about CMV? •  We care about correlation accuracies •  It is a significant problem that accounts for up to 27% of variation observed in social science research ( Lindell and Whitney 2001). •  Identifying the degree of CMV is important because it declares the validity of observed relationships (Podsakoff et al 2003; Malhotra, Kim et al 2006).
  • 6. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Example Hypothesis: Higher Enjoyment in work training (eg. NewMR webinar), leads to Workplace Loyalty Enjoyment    in   work  training   Workplace   Loyalty     -­‐  0.65   0.55  
  • 7. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Major Sources of CMV? -  Social desirability (Ganster et al 1983) -  Ambiguous wording (Hufnagle and Conca 1994) -  Scale length (Harrison et al 1996)
  • 8. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Source  Categories     Explana*on   Type  of  Bias     Common  Rater  Effects     Arises  when  the   ques=onnaire  brings  forth   changes  in  the   respondent’s  mood  and   cogni=ve  processing   (Podsakoff  et  al  2003;   Lindell  &  Whitney  2001)     Acquiesence  bias     -­‐ Agreeing  to  everything   -­‐ Extreme  responses       Item  demand   characteris*cs  ,       Item   context  effects  and     Measurement  context     effects       -­‐ Context  induced  mood   -­‐ Social  desirability     Response  style  bias       -­‐  Over-­‐repor@ng  socially   desirable  behaviours,  and   under  repor@ng  socially   undesirable  behaviours     Sources of CMV?
  • 9. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Measurement Instrument 1.  Check for the sensitivity of Questions -  Sensitive questions can lead to systematic misreporting because of social desirability 2. Questionnaire length and order of questions -  The longer the questionnaire, the more issue of social desirability (Holtgraves 2004)
  • 10. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Mode of Administration 1.  Paper -  Check for visual design effects -  Limit visual stimulus
  • 11. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Mode of Administration 2. Online –  Online – screensize, configuration, compatibility with operation system and harware used by responsdent (Dillman 2007) –  Previous research shows that answers to online survey questions are affected by design choices – eg. ordering of questions (Dillman 2007; Couper et al 2001), layout (Winter 2002; Christian 2003; Toepel et al 2006) –  Grouping related items on a single screen is likely to lead respondents to view the items as related entities. Thus, increasing the correlation among them (Strack, Schwarz and Wanke 1991; Schwarz and Sudman 1996; Tourangeau et al 2004; Dillman 2007) •  Correlations are higher for items that appear together on a screen than among items separated across several screens (Couper, Traugott and Lamias 2001; Tourangeau et al 2004; Peytchev et al 2006)
  • 12. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 How  much  do  you  enjoy  work  training?   Please  indicate  how  much  you  agree  to  the  following  statement  on  your  sense  of  enjoyment  with  work  training   Completely disagree   Barely agree   Slightly Agree   Moderately Agree   Agree   Highly Agree   Completely Agree   I feel energised when I participate in training sessions at work   ¡   ¡   ¡   ¡   ¡   ¡   ¡   I feel motivated when we have training at work   ¡   ¡   ¡   ¡   ¡   ¡   ¡   Work training is fun   ¡   ¡   ¡   ¡   ¡   ¡   ¡   I feel happy during training activites   ¡   ¡   ¡   ¡   ¡   ¡   ¡   How  do  you  feel  about  your  workplace?   Please  indicate  how  much  you  agree  to  the  following  statement  on  how  you  feel  about  your  workplace   Completely disagree   Barely agree   Slightly Agree   Moderatel y Agree   Agree   Highly Agree   Completely Agree   I am committed to my workplace   ¡   ¡   ¡   ¡   ¡   ¡   ¡   I love the company I work for   ¡   ¡   ¡   ¡   ¡   ¡   ¡   I always work for the success of the company I work for   ¡   ¡   ¡   ¡   ¡   ¡   ¡   I want to stay in this workplace forever   ¡   ¡   ¡   ¡   ¡   ¡   ¡   2 scales in one screen – not recommended especially if constructs are hypothesised to be correlated
  • 13. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 1 scale – recommended How  much  do  you  enjoy  work  training?   Please  indicate  how  much  you  agree  to  the  following  statement  on  your  sense  of  enjoyment  with  work  training   Completely disagree   Barely agree   Slightly Agree   Moderately Agree   Agree   Highly Agree   Completely Agree   I feel energised when I participate in training sessions at work   ¡   ¡   ¡   ¡   ¡   ¡   ¡   I feel motivated when we have training at work   ¡   ¡   ¡   ¡   ¡   ¡   ¡   Work training is fun   ¡   ¡   ¡   ¡   ¡   ¡   ¡   I feel happy during training activites   ¡   ¡   ¡   ¡   ¡   ¡   ¡  
  • 14. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Correlation comparisons Correla*on  Coefficient   2  Scales  in  1  screen   0.76**   1  construct  in  1  screen   0.55***   Hypothesis:  Higher    Enjoyment  in  work  training  (eg.  NewMR   webinar),    leads  to  Workplace  Loyalty       ***p  <  0.001   **  p  <0.01  
  • 15. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Mode of Administration 3. Telephone interviews -  Socio-cultural impact of interviewers -  Mode effect -  Respondents at home vs somewhere else (mobile respondents) -  Consider dual-frame methodology -  Respondent familiarity with interviewers or company (longitudinal studies)
  • 16. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Statistically Testing for CMV -  Harman’s Common Factor -  Partial correlation procedure - Marker Variable Technique
  • 17. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Thank you Mavi Glinoga
  • 18. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Q & A Mavi Glinoga Monash University Sue York NewMR
  • 19. Mavi Glinoga PhD, Monash University, Australia NewMR Advances in Quantitative Research Event, 19 September 2012, Session 1 Thank you Mavi Glinoga Email: maviglinoga@gmail.com LinkedIn: Mavi Glinoga Twitter: @Mavi_Glinoga
  • 20. A  Presenta*on  from  The  NewMR  “Advances  in   Quan*ta*ve  Research”  Event   19  September,  2012   Event  sponsored  by  Affinnova   All  copyright  owned  by  The  Future  Place  and  the  presenters  of  the  material   For  more  informa=on  about  Affinnova  visit  www.affinnova.com   For  more  informa=on  about  NewMR  events  visit  newmr.org   Common  Method  Variance  –  A  threat  to  Quality  of   data     Mavi  Glinoga  PhD,  Monash  University