5 confirmatory factor analysis -...

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5 Confirmatory Factor Analysis

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5.1 INTRODUCTION

The hypothesized model of the study consists of 11 factors which were

originally measured using a questionnaire of 57 statements. Previous analysis of the

collected data resulted into the elimination of 4 items and hence, 53 items were taken

further for confirmatory factor analysis. This chapter presents the confirmatory

analysis carried out before the hypothesized model is tested for its fitness.

The objective of this chapter is to develop the measurement model of the study

variables. First section of the chapter presents an overview of CFA while the second

section describes the procedure adopted for conducting analysis along with the criteria

used for improving the measurement model. The third section of the chapter describes

the CFA for individual factors. Finally, the fourth section presents the CFA for overall

model.

5.2 CFA - OVERVIEW

Confirmatory factor analysis (CFA) is a statistical technique used to verify the

factor structure of a set of observed variables. In a CFA the researcher has a strong

idea about the number of factors, the relations among the factors, and the relationship

between the factors and measured variables. In exploratory factor analysis, factors

underlying a set of scale items are not known while extracting the factors. In

confirmatory factor analysis, the loading of scale items on factors are already known

through the theory and they are tested for such loadings to fit an observed set of data.

CFA is commonly used for establishing the validity of a single factor model, test the

significance of a specific factor loading, test whether a set of factors are correlated or

uncorrelated and assess the convergent and discriminant validity of a set of measures

(DeCoster, 1998).

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5.3 ANALYSIS PROCEDURE

The measurement model is evaluated in two steps.

Step 1 CFA is conducted for each identified factor of the measurement model.

Step 2 CFA is conducted for all factors at the same time for getting the final

measurement model

In step 2, individual scale items were loaded on their appropriate factors and

all factors were correlated with each other.

5.4 EVALUATION CRITERIA FOR MEASUREMENT MODEL

The measurement model in step one and two are evaluated using the following

model fit indices as proposed by Byrne (2001), Hair, Anderson, Tatham, & Black

(1998) and Kumar (2010):

(i). 2 test

(ii). 2/df ratio

(iii). Comparative Fit Index (CFI)

(iv). Goodness-of-Fit Index (GFI)

(v). Root Mean Square Error of Approximation (RMSEA)

For improving the model, following test statistics are used (Kumar, 2010):

(i). Standardized Regression Weights (SRW)

(ii). Standardized Residual Covariances (SRC)

(iii). Modification Indices (MI)

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2 2/df ratio are highly sensitive to the sample size In case of large

sample, these two statistics were not applicable to assess the fitness of the study

model (Garson, 2010; Ullman, 1996; Schumacker & Lomax, 2004). So, CFI, GFI and

RMSEA are utilized to assess the model fitness as fit indices.

The acceptance rules of the above indices and statistics are shown in the

Tables 5.1 and 5.2 respectively.

Table 5.1 Model Fit Indices

Fit Index Values Model Fitness

CFI

< 0.80 Unacceptable

0.80 to 0.90 Acceptable

> 0.90 Good

GFI

< 0.80 Unacceptable

0.80 to 0.90 Acceptable

> 0.90 Good

RMSEA

< 0.05, Good

< 0.08 Acceptable

< 0.10 Mediocre

poor

Table 5.2 Model Evaluation Test Statistics

Statistic Value Criteria Model Improvement

SRW Acceptable Not Required

< 0.4 Unacceptable Required

SRC - 2.58 to 2.58 Acceptable Not Required

Otherwise Unacceptable Required

MI < 10 Acceptable Not Required

Unacceptable Required

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Table 5.1 is used for individual factors and overall model fitness and Table 5.2

is used to improve the model. Model improvement is made by eliminating or

correlating the measurement item which has low SRW, high SRC, and high MI.

5.5 MEASUREMENT MODEL TESTING

5.5.1 CFA for Each Factor

CFA was conducted for the following eleven individual factors of the

measurement model:

i) pleasure, ii) arousal, iii) merchandise quality, iv) service quality, v) perceived price, vi) ambient lighting,

vii) background music, viii) ambient scent, ix) in-store signage and graphics,

x) store satisfaction and xi) store loyalty.

5.5.1.1 Pleasure Factor CFA

The pleasure factor consists of five measurement items (PL2, PL3, PL4, PL5,

PL6) for CFA. The results of the CFA for pleasure model are shown in Table 5.3.

Table 5.3 CFA Results for Pleasure Factor

No. of Items

2 (df) 2/df CFI GFI RMSEA Remarks

Initial Model Results 5 384.218(5) 76.844 0.785*** 0.796*** 0.353***

Item PL5 is eliminated

in modification

Refined Model Results

4 126.083(2) 63.041 0.907* 0.912* 0.319***

Final Refined Model Results

4 10.842(1) 10.842 0.993* 0.991* 0.096**

* Indicates fit is good ** indicates fit is acceptable *** indicates fit is unacceptable

CFI, GFI and RMSEA of the initial model are unacceptable. So, model

improvement is required. For improving the model, item PL5 is eliminated based on

the statistics SRC and MI as reported in Tables 5.5 and 5.6. The SRC between PL5

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and PL4 is high (9.283) and MI between PL4 and PL5 are also high (136.948 and

139.921) and unacceptable. Hence, the item PL5 is eliminated for improvement.

Table 5.4 Standardized Regression Weights for Pleasure Scale Items

SRW

PL6 <--- Pleasure 0.860





Table 5.5 Standardized Residual Covariance among Pleasure Scale Items

PL2 PL3 PL4 PL5 PL6

PL2 0.000 PL3 -0.901 0.000 PL4 1.624 -1.664 0.000 PL5 0.821 -0.754 9.283 0.000 PL6 0.079 1.636 -3.041 -2.538 0.000

Table 5.6 Modification Indices among Pleasure Scale Items

MI

PL2 <--- PL4 23.491

PL3 <--- PL4 10.817

PL3 <--- PL6 12.985

PL4 <--- PL5 136.948

PL4 <--- PL6 16.407

PL5 <--- PL4 139.921

PL5 <--- PL6 11.765

PL6 <--- PL3 20.988

PL6 <--- PL4 59.888

PL6 <--- PL5 42.032

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CFA was conducted after eliminating the item PL5. The model fit results are

shown in Table 5.3. The RMSEA of refined model is unacceptable. So, further

improvement of the model is required. For improving the model PL2 and PL4 are

correlated based on SRC and MI statistics (Table 5.8 and 5.9). The SRC is high

(3.746) between PL2 and PL4 and the MI values are also high (75.230 and 20.840)

between PL2 and PL4. Hence, PL2 and PL4 were correlated.

Table 5.7 Standardized Regression Weights of Pleasure Scale Items

SRW





Table 5.8 Standardized Residual Covariance among Pleasure Scale Items

PL2 PL3 PL4 PL6

PL2 0.000 PL3 -0.682 0.000 PL4 3.746 -0.443 0.000 PL5 -0.036 0.437 -1.980 0.000

Table 5.9 Modification Indices among Pleasure Scale Items

MI

PL2 <--- PL4 75.230

PL4 <--- PL2 20.846

PL6 <--- PL4 45.660

After correlating PL2 and PL4, the CFA was conducted again. As shown in

Table 5.3, the model fit indices of final model i.e., CFI, GFI and RMSEA, indicate

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that the refined pleasure factor is acceptable for structural equation model. The path

diagram for refined pleasure factor is shown in Figure 5.1.

Figure 5.1 Path Diagram for Refined Pleasure Factor

5.5.1.2 Arousal Factor CFA

The arousal factor consists of five measurement items (AR1, AR2, AR3, AR4,

AR6) for CFA. The results of the CFA for arousal model are shown in Table 5.10.

Table 5.10 CFA Results of Arousal Factor

No. of Items


Initial Model Results 5 237.964(5) 47.593 0.772*** 0.871** 0.276*** Item AR6 is

eliminated in

modification Final Refined Model Results 4 22.601(2) 11.301 0.972* 0.983* 0.083**


Except for GFI, CFI and RMSEA indicate unacceptable values for model

fitness. So, model improvement is required. For improving the model, item AR6 is

eliminated based on the statistic SRW as reported in Table 5.11. The value of SRW

for AR6 is 0.388 which is lower than the cut off value of 0.4. Hence, item AR6 is

eliminated for improvement.

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Table 5.11 Standardized Regression Weights for Arousal Scale Items

SRW

AR6 <--- Arousal 0.388





Table 5.12 Standardized Residual Covariance among Arousal Scale Items

AR1 AR2 AR3 AR4 AR6

AR1 .000 AR2 -1.499 .000 AR3 .837 .328 .000 AR4 .171 .228 -1.538 .000 AR6 -1.752 5.258 -2.769 7.506 .000

Table 5.13 Modification Indices among Arousal Scale Items

MI

AR1 <--- AR2 10.516

AR1 <--- AR6 12.583

AR2 <--- AR6 55.015

AR3 <--- AR4 12.862

AR3 <--- AR6 38.938

AR4 <--- AR6 85.195

AR6 <--- AR2 35.572

AR6 <--- AR3 10.246

AR6 <--- AR4 71.128

After deleting item AR6, CFA was conducted again. The values of CFI, GFI

and RMSEA, as shown in Table 5.10, for the refined model indicate that the improved

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arousal factor is acceptable. The path diagram for refined arousal factor is shown in

Figure 5.2.

Figure 5.2 Path Diagram for Refined Arousal Factor

5.5.1.3 Merchandise Quality Factor CFA

The merchandise quality factor consists of six measurement items (MQ1,

MQ2, MQ3, MQ4, MQ5, MQ6) for CFA. The results of the CFA for merchandise

quality model are shown in Table 5.14.

Table 5.14 CFA Results for Merchandise Quality Factor

No. of Items


Initial Model Results 6 96.395(9) 10.711 0.933* 0.949* 0.126*** Item MQ3 is

eliminated in



The CFI and GFI values indicate that the merchandise quality factor has a

good model fit. But RMSEA value indicates unacceptability of the model fitness.

Hence, model improvement is carried out by eliminating item MQ3 and correlating

items MQ1 and MQ2. The item MQ3 is eliminated because of low SRW of 0.384

(Table 5.15) which is below the cut off value of 0.4. The items MQ1 and MQ2 are

correlated because the SRC and MI values between MQ1 and MQ2 are well beyond

the cut off values (Tables 5.16 and 5.17).

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Table 5.15 Standardized Regression Weights for Merchandise Quality Scale Items

SRW

MQ6 <--- Merchandise Quality 0.795






Table 5.16 Standardized Residual Covariance among Merchandise Quality Scale Items

MQ1 MQ2 MQ3 MQ4 MQ5 MQ6

MQ1 0.000 MQ2 4.310 0.000 MQ3 -0.085 1.730 0.000 MQ4 -0.284 0.195 0.970 0.000 MQ5 -1.052 -2.006 -1.176 0.344 0.000 MQ6 -0.378 -0.205 -0.683 -0.476 0.949 0.000

Table 5.17 Modification Indices among Merchandise Quality Scale Items

MI

MQ1 <--- MQ2 31.486

MQ2 <--- MQ1 33.538

MQ5 <--- MQ2 15.986

After deleting the item MQ3 and correlating items MQ1 and MQ2, CFA was

conducted again. The results of the improved model are shown in Table 5.14. The

values of CFI, GFI and RMSEA of the refined merchandise quality factor are

acceptable for the structural equation model. The path diagram for refined

merchandise quality factor is shown in Figure 5.3.

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Figure 5.3 Path Diagram for Refined Merchandise Quality Factor

5.5.1.4 Service Quality Factor CFA

The service quality factor consists of five measurement items (SQ1, SQ2,

SQ3, SQ4, SQ5) for CFA. The results of the CFA for service quality model are shown

in Table 5.18.

Table 5.18 CFA Results for Service Quality Factor

No. of Items


Initial Model Results 5 96.250(5) 19.250 0.903* 0.937* 0.173*** No item is

eliminated in



The model fitness results for CFI and GFI show good fit of the service quality

model while RMSEA indicate unacceptable model fitness. Hence, model

improvement is required. Based on the values of SRCs and MIs, model improvement

is done by correlating items SQ2 with SQ3 and SQ1 with SQ4. As shown in Table

5.20, the SRC between SQ2 and SQ3 is 2.769 and SRC between SQ1 and SQ4 is

2.622 which are above the cut off value of 2.58. The values of MI between SQ1 and

SQ4 are 14.212 and 20.607 and between SQ2 and SQ3 are 16.708 and 28.486 which

are also high (Table 5.21). So, SQ1 is correlated with SQ4 and SQ2 is correlated with

SQ3.

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Table 5.19 Standardized Regression Weights for Service Quality Scale Items

SRW

SQ5 <--- Service Quality 0.680





Table 5.20 Standardized Residual Covariance among Service Quality Scale Items

SQ1 SQ2 SQ3 SQ4 SQ5

SQ1 0.000 SQ2 -1.591 0.000 SQ3 -1.876 2.769 0.000 SQ4 2.622 -2.003 -0.368 0.000 SQ5 0.799 -0.397 -0.309 0.134 0.000

Table 5.21 Modification Indices among Service Quality Scale Items

MI

SQ1 <--- SQ4 14.212

SQ2 <--- SQ3 16.708

SQ3 <--- SQ1 12.992

SQ3 <--- SQ2 28.486

SQ4 <--- SQ1 20.607

SQ4 <--- SQ2 12.095

After correlations are made, CFA was conducted. The improved fit indices for

refined service quality factor are shown Table 5.18. CFI, GFI and RMSEA values for

the refined model show acceptable fit for the improved service quality model. The

path diagram for refined service quality factor is shown in Figure 5.4.

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Figure 5.4 Path Diagram for Refined Service Quality Factor

5.5.1.5 Perceived Price Factor CFA

The perceived price factor consists of four measurement items (PP1, PP2, PP3,

PP4) for CFA. The results of the CFA for perceived price model are shown in Table

5.22.

Table 5.22 CFA Results for Perceived Price Factor

No. of Items


Initial Model Results 4 11.810(2) 5.905 0.991* 0.990* 0.090** No model

improvement required Final Refined

Model Results 4 -- -- -- -- --


CFI, GFI and RMSEA values show good fit for perceived price factor. Hence,

model improvement is not required for perceived price factor. The path diagram for

the perceived price is shown in Figure 5.5.

Figure 5.5 Path Diagram for Perceived Price Factor

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5.5.1.6 Ambient Lighting Factor CFA

The ambient lighting factor consists of seven measurement items (AL1, AL2,

AL3, AL4, AL5, AL6, AL7) for CFA. The results of the CFA for ambient lighting

model are shown in Table 5.23.

Table 5.23 CFA Results for Ambient Lighting Factor

No. of Items


Initial Model Results 7 198.162(14) 14.154 0.906* 0.917* 0.147***

Item AL1 is eliminated

in modification

Refined Model Results 6 80.654(9) 8.962 0.954* 0.957* 0.114***

Final Refined Model Results 6 45.250(8) 5.656 0.976* 0.976* 0.087**


The model fitness results for CFI and GFI show good fit of the ambient

lighting model while RMSEA value indicate unacceptable model fitness. Hence,

model improvement is required. For improving the model, item AL1 is deleted based

on SRC and MI values. As can be seen in Table 5.25, SRC values associated with

AL1 are high (2.866 with AL2 and -3.155 with AL3). The MI values associated with

AL1 are also high (18.812 and 23.784 with AL2, 22.02 and 22.069 with AL3 and

12.562 with AL4). So, AL1 is eliminated from the model.

Table 5.24 Standardized Regression Weights for Ambient Lighting Scale Items

SRW

AL7 <--- Ambient Lighting 0.841







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Table 5.25 Standardized Residual Covariance among Ambient Lighting Scale Items

AL1 AL2 AL3 AL4 AL5 AL6 AL7

AL1 0.000 AL2 2.866 0.000 AL3 -3.155 0.487 0.000 AL4 -1.984 -1.035 2.189 0.000 AL5 0.942 -2.727 0.091 1.689 0.000 AL6 0.622 -1.035 -0.035 -0.057 1.509 0.000 AL7 0.196 0.762 -0.318 -0.050 -0.778 -0.131 0.000

Table 5.26 Modification Indices among Ambient Lighting Scale Items

MI

AL1 <--- AL2 18.812

AL1 <--- AL3 22.020

AL2 <--- AL1 23.784

AL2 <--- AL5 21.062

AL3 <--- AL1 22.069

AL3 <--- AL4 11.129

AL4 <--- AL1 12.562

AL4 <--- AL3 15.303

AL5 <--- AL2 15.013

After eliminating AL1, CFA was conducted. The improved model fit indices

is shown in Table 5.23. Since RMSEA values indicate unacceptable model fitness,

further improvement is required. For further improving the model, items AL2 and

AL7 are correlated based on MI values in Table 5.29.

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Table 5.27 Standardized Regression Weights of Ambient Lighting Scale Items

SRW







Table 5.28 Standardized Residual Covariance among Ambient Lighting Scale Items

AL2 AL3 AL4 AL5 AL6 AL7

AL2 0.000 AL3 0.454 0.000 AL4 -0.942 1.256 0.000 AL5 -2.301 -0.315 1.343 0.000 AL6 -0.455 -0.445 -0.376 1.620 0.000 AL7 1.475 -0.724 -0.351 -0.618 0.136 0.000

Table 5.29 Modification Indices among Ambient Lighting Scale Items

MI

AL2 <--- AL5 13.419

AL5 <--- AL2 10.576

AL7 <--- AL2 12.851

CFA was conducted again after the items AL7 and AL2 are correlated. Table

5.23 shows the refined model fit indices. CFI, GFI and RMSEA values show that the

refined ambient lighting model has acceptable fit. The path diagram for the refined

ambient lighting factor is shown in Figure 5.6.

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Figure 5.6 Path Diagram for Refined Ambient Lighting Factor

5.5.1.7 Background Music Factor CFA

The background music factor consists of four measurement items (BM2, BM3,

BM4, BM5) for CFA. The results of the CFA for background music model are shown

in Table 5.30.

Table 5.30 CFA Results for Background Music Factor

No. of Items






CFI, GFI and RMSEA values show good fit for background music factor.

Hence, model improvement is not required for background music factor. The path

diagram for the background music is shown in Figure 5.7.

Figure 5.7 Path Diagram for Background Music Factor

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5.5.1.8 Ambient Scent Factor CFA

The ambient scent factor consists of four measurement items (AS1, AS2, AS3,

AS4) for CFA. The results of the CFA for ambient scent model are shown in Table

5.31.

Table 5.31 CFA Results for Ambient Scent Factor

No. of Items






CFI, GFI and RMSEA values show good fit for ambient scent factor. Hence,

model improvement is not required for ambient lighting factor. The path diagram for

the ambient scent is shown in Figure 5.8.

Figure 5.8 Path Diagram for Ambient Scent Factor

5.5.1.9 In-store Signage and Graphics Factor CFA

The in-store signage and graphics factor consists of four measurement items

(SG2, SG3, SG4, SG5) for CFA. The results of the CFA for in-store signage and

graphics model are shown in Table 5.32.

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Table 5.32 CFA Results for In-store Signage and Graphics

No. of Items






CFI, GFI and RMSEA values show good fit for in-store signage and graphics

factor. Hence, model improvement is not done for in-store signage and graphics

factor. The path diagram for the in-store signage and graphics is shown in Figure 5.9.

Figure 5.9 Path Diagram for In-store Signage and Graphics

5.5.1.10 Store Satisfaction Factor CFA

The store satisfaction factor consists of four measurement items (SS1, SS2,

SS3, SS4) for CFA. The results of the CFA for store satisfaction model are shown in

Table 5.33.

Table 5.33 CFA Results for Perceived Price Factor

No. of Items






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CFI, GFI and RMSEA values show good fit for store satisfaction factor.

Hence, model improvement is not required for store satisfaction factor. The path

diagram for the store satisfaction model is shown in Figure 5.10.

Figure 5.10 Path Diagram for Store Satisfaction Factor

5.5.1.11 Store Loyalty Factor CFA

The store loyalty factor consists of five measurement items (SL1, SL2, SL3,

SL4, SL5) for CFA. The results of the CFA for store loyalty model are shown in

Table 5.34.

Table 5.34 CFA Results for Store Loyalty Factor

No. of Items


Initial Model Results 5 199.204(5) 39.841 0.906* 0.884** 0.252***

Item SL4 is eliminated

in modification

Refined Model Results 4 36.808(2) 18.404 0.976* 0.973* 0.169***

Final Refined Model Results 4 2.591(1) 2.591 0.999* 0.998* 0.051*


The model fitness results for CFI and GFI show good and acceptable fits of

the store loyalty model while RMSEA indicate unacceptable model fitness. Hence,

model improvement is required. For improving the model, item SL4 is eliminated.

Item SL4 is eliminated based on the values of SRC and MI as shown in Tables 5.36

and 5.37. The SRC value between SL2 and SL4 (2.883) is high. The MI values

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associated with SL4 (10.635 with SL1, 46.258 and 32.817 with SL2) are also high.

So, item SL4 is eliminated for improvement.

Table 5.35 Standardized Regression Weights for Store Loyalty Scale Items

SRW

SL5 <--- Store Loyalty 0.786





Table 5.36 Standardized Residual Covariance among Store Loyalty Scale Items

SL1 SL2 SL3 SL4 SL5

SL1 0.000 SL2 -0.008 0.000 SL3 1.019 -1.473 0.000 SL4 -1.227 2.883 -1.026 0.000 SL5 -0.223 -0.661 1.231 -0.451 0.000

Table 5.37 Modification Indices among Store Loyalty Scale Items

MI

SL1 <--- SL4 10.635

SL2 <--- SL3 12.651

SL2 <--- SL4 46.258

SL3 <--- SL2 12.828

SL4 <--- SL2 32.817

CFA was conducted after eliminating SL4. The improved model fit statistics

are shown in Table 5.34. Except RMSEA, CFI and GFI values indicate the store

loyalty model is fit. Hence, further improvement is required. For improving the

model, items SL2 and SL3 are correlated based on MI values as shown in Table 5.40.

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The modification index between SL2 and SL3 is 17.554 which is higher than cut off

value of 10. So, SL2 and SL3 are correlated

Table 5.38 Standardized Regression Weights for Store Loyalty Scale Items

SRW





Table 5.39 Standardized Residual Covariance among Store Loyalty Scale Items

SL1 SL2 SL3 SL5

SL1 0.000 SL2 0.640 0.000 SL3 0.074 -0.932 0.000 SL5 -0.688 0.261 0.684 0.000

Table 5.40 Modification Indices among Store Loyalty Scale Items

MI

SL2 <--- SL1 10.482

SL3 <--- SL2 17.554

SL5 <--- SL1 13.558

SL5 <--- SL3 10.605

CFA was conducted again after correlating the items SL2 and SL3. The

improved model indices of CFI, GFI and RMSEA depicted in the Table 5.34 indicate

that the final refined store loyalty model is acceptable for structural equation model.

The path diagram for refined store loyalty factor is shown in Figure 5.11.

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Figure 5.11 Path Diagram for the Refined Store Loyalty Factor

A summary of the CFA results done on each of the factors is shown in Table

5.41 below. The fit statistics reported in the table are of the refined models of each

factor.

Table 5.41 Fit Statistics of CFA for Each Factor - Refined Models

Factor No. of Scale Items

2 (df) 2/df CFI GFI RMSEA

Refined Model (Total No. of Scale Items = 48)

Pleasure 4 10.842(1) 10.842 0.993 0.991 0.096

Arousal 4 22.601(2) 11.301 0.972 0.983 0.083 Merchandise Quality 5 24.917(4) 6.229 0.983 0.985 0.093

Service Quality 5 11.643(3) 3.881 0.991 0.992 0.069

Perceived Price 4 11.810(2) 5.905 0.991 0.990 0.090

Ambient Lighting 6 45.250(8) 5.656 0.976 0.976 0.087

Background Music 4 13.093(2) 6.546 0.995 0.989 0.095

Ambient Scent 4 9.584(2) 4.792 0.992 0.992 0.079 In-store Signage and Graphics 4 6.224(2) 3.112 0.995 0.995 0.059

Store Satisfaction 4 7.885(2) 3.942 0.995 0.994 0.069

Store Loyalty 4 2.591(1) 2.591 0.999 0.998 0.051

5.5.2 CFA for Overall Measurement Model

After conducting CFA for each factor in the first step of measurement model

testing, the CFA is performed for all the factors at the same time in step 2. In this step,

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individual scale items were loaded on their appropriate factors and all factors were

correlated with each other.

CFA was conducted for the measurement model that is comprised of 11

factors measured by 48 scale items. The results of CFA for the overall measurement

model are shown in Table 5.42.

Table 5.42 CFA Results for Overall Measurement Model

No. of Items


Initial Model Results

48 4887.590(1019) 4.796 0.813** 0.739*** 0.079**

Items SS1, SQ1, AR3,

SL5, PL4 and AR1 are

eliminated in modification

Refined Model Results

42 3337.989(761) 4.386 0.854** 0.796*** 0.075**

Final Refined Model Results

42 2852.743(681) 4.189 0.869** 0.808** 0.072**


The initial model values of CFI and RMSEA indicate that the measurement

model fit is acceptable but the value of GFI show unacceptable fit of the measurement

model. Hence, measurement model improvement is required. For improving the

model, the items SS1, SQ1, AR3, SL5, PL4 and AR1 are eliminated. The SRW value

of AR1 (0.367) is below the cut off value of 0.4 and SRW for PL4 (0.423) is lowest of

the accepted values. The SRC values associated with the items SS1, SQ1, AR3 and

SL5 are very high and unacceptable. So, items SS1, SQ1, SQ4, SL2, PL4 and AR1

are eliminated and CFA was conducted for getting the refined model results.

In the refined model, fit indices, CFI and RMSEA, indicate that the

measurement model fit is acceptable but the value of GFI show unacceptable fit.

Hence, further model improvement is required. For improving further, six pairs of

items were correlated; AL6 and AL7, AL4 and AL6, AL2 and AL5, MQ2 and MQ5,

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PP2 and PP4, and PP3 and PP4. These pairs of items are correlated because the SRCs

between these items are high and unacceptable. After these modifications, CFA was

conducted again. The final refined model CFA results are shown in Table 5.42.

The values of CFI, GFI and RMSEA of the final refined model show

acceptable fit. This final refined model is taken as the structural model of the study for

testing the devised hypotheses. The path diagram of the final refined measurement

model is shown in Figure 5.12.

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Figure 5.12 Path Diagram of Final Refined Measurement Model

5 confirmatory factor analysis -...

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