Measuring Family Early Literacy Practices Across Diverse ......measuring family early literacy...
1
ABSTRACT The purpose of this presentation is to assess the psychometric properties of a self-report questionnaire measuring family early literacy practices (FELP). Rash analysis was conducted to evaluate item response patterns across diverse subgroups. Preliminary findings indicate the FELP is a reliable and valid measure for assessing family early literacy practices. Session attendees will learn about the validation of a self-report questionnaire. The benefits of analyzing item response patterns among diverse populations will be discussed. INTRODUCTION -Whitehurst and colleagues have found positive correlations and longitudinal stability between early literacy skills and later reading skills, which supports the need for early intervention (1999). -Researchers have determined that indicators of a rich home environment include parent and guardians’ responsiveness to their children’s early literacy abilities, involvement with their children in language and literacy-based activities and routines, and the provision of literacy materials (Hart & Risley, 1995; Roberts, Jurgens, & Burchinal, 2005). -As children generally spend a large portion of time with their families, family involvement in literacy activities is strongly related to child achievement (Evans, 1998). -Recent research has investigated the relationship between parental beliefs and behaviors regarding literacy and outcome of their children (Meagher, Arnold, Doctoroff & Baker, 2008; Weigel, Martin, & Bennet, 2006). -It has been hypothesized that these behaviors and expectations manifest as literacy promoting behaviors which benefit child learning (Goodnow & Collins, 1990; Roskos & Christie, 2000). -The present study examines the psychometric properties of the family early literacy practices (FELP) questionnaire in a large and diverse sample of preschool age children from Jacksonville, Florida. The aim of the study is to answer the following questions: 1 ∙ Does the original factor structure of the FELP remain consistent for a large and diverse sample of preschool-age children? 2 ∙ Do item response patterns differ among diverse subgroups (e.g. native versus non-native English speakers)? DISCUSSION 1 ∙ Results indicate the FELP has good reliability and validity for parents of preschool age children. 2 ∙ Exploratory factor analysis of the FELP yielded support for a five-factor model, which aligned with the theoretical construct of the FELP. 3 ∙ Internal consistency of the FELP was satisfactory. However the reliability coefficient of the modeling and monitoring factor of the FELP was below acceptable limits (Cronbach’s alpha = .67). This is not surprising given the fact that this FELP factor only consists of four items. 4 ∙ This study also provides support for the construct validity of the FELP for parents of preschool age children. Rasch analysis revealed that the threshold for four of the five factors (exception was Modeling and Monitoring) was in the appropriate order. This means the thresholds increased in a positive direction as the category label increased. 5 ∙ The people mean measure for Expectations was the highest at .69, which is more than two-thirds of a standard deviation above the mean of the items. This demonstrates that people typically endorsed many positive items for the Expectation factor, which ask parent’s about their beliefs about their children’s future education. The high mean measures for this scale suggest that most people positively endorsed those items. This finding is not surprising given that you might expect parents to believe positively about their children’s academic future. 6 ∙ Rasch analysis supported the reliability findings from the factor analysis. 7 ∙ Rasch analysis demonstrates that response patterns varied by primary language spoken in the home for all 5 factors. Future Research: ◦ Include preschool age children who may not be attending a formal preschool setting in an effort to include a more diverse sample in future studies. ◦ Evaluate DIF between diverse subgroups. ◦ Conduct validity and reliability assessments of the FELP in Spanish with Spanish speaking families to investigate whether this measure translates to a Spanish speaking population. ◦ Compare the family measures to child outcome data with a diverse population. References: Evans, M. (1998). Parental involvement in beginning reading: Preliminary report from a three year longitudinal study. Canadian Journal of School Psychology, 14(1), 11-20. Goodnow, J. J. & Collins, A. W. (1990). Development according to parents: The nature, sources, and consequences of parents' ideas. Hillsdale, NJ, England: Lawrence Erlbaum Associates, Inc. Hart, B., & Risley, T. R. (1980). In vivo language intervention: Unanticipated general effects. Journal of Applied Behavior Analysis,13(3), 407-432. Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47, 149 –74. Meagher, S. M., Arnold, D. H., Doctoroff, G. L., & Baker, C. N. (2008). The relationship between maternal beliefs and behavior during shared reading. Early Education and Development, Special Issue: Parent-Child Interaction and Early Literacy Development, 19(1), 138-160. Roberts, J., Jurgens, J., & Burchinal, M. (2005). The role of home literacy practices in preschool children's language and emergent literacy skills. Journal of Speech, Language, and Hearing Research, 48(2), 345- 359. Roskos, K. A. & Christie, J. F. (2000). Play and literacy in early childhood: Research from multiple perspectives. Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers. Weigel, D. J., Martin, S. S., & Bennett, K. K., (2006). Contributions of the Home Literacy Environment to Preschool-Aged Children's Emerging Literacy and Language Skills. Early Child Development and Care, 176(3- 4), 357-378. Whitehurst, G. J., Zevenbergen, A. A., Crone, D. A., Schultz, M. D., Velting, O. N., & Fischel, J. E. (1999). Outcomes of an emergent literacy intervention from Head Start through second grade. Journal of Educational Psychology, 91(2), 261-272. METHOD Participants • 2079 parents of preschool age children (48.6% female and 48.8% male) from a variety of educational preschool settings in Jacksonville, Florida. • Education: 43.7% Bachelors or higher, 49.7% HS or Some College, 5% No HS Diploma. • Income: 27.2% over $75K, 28.5% $40-74K, 37.4% under $40K. • Ethnicity: 53.1% White, 21.4% Black, 24.1% Other. • Language: 86.7% English, 11.2% Other. • Parents completed the FELP questionnaire. • Multiple imputation enabled all participant information to remain. Instrumentation • The FELP is a research-developed questionnaire (Likert Scale). • There are 5 factors: Skill Building, Interactive Reading/ Enjoyment, Modeling and Monitoring, Expectations, and Child Skill. • Parental Behaviors: Skill Building, Interactive Reading/ Enjoyment, and Modeling and Monitoring. • Parental Beliefs: Expectations and Child Skill. • Exploratory Factor Analysis used to obtain factors (majority Caucasian middle-class families) revealed the FELP had 5 robust factors with adequate alpha coefficients ranging from .77 to .87. Measuring Family Early Literacy Practices Across Diverse Preschool Families Data Analysis -Exploratory factor analysis • Examine the factor structure of the FELP. -Reliability • Internal consistency coefficients (Cronbach’s alphas) and item-total correlations of the total scale and subscales of the FELP. -Rasch Analysis • Examine the construct of the FELP. • The Rating Scale Model (RSM), used to test the unidimensionality of each hypothesized factor (Andrich, 1978; Masters, 1982). • DIF was used to evaluate the item response pattern among diverse subgroups. An acceptable range for the t value is between -2 to 2 (Bond & Fox, 2007). FELP Questionnaire 4 FELP Factor Structure Factor Loadings Factor Correlation Matrix Dr. Laura Bailet, Dr. Suzanne Murphy, and Dr. Cynthia Zettler-Greeley Nemours BrightStart! Dyslexia Initiative Jacksonville, FL Kandia Lewis and Dr. Marika Ginsburg-Block University of Delaware Newark, DE FELP Factor Structure F1-SB F2-IR F3-MM F4- Ex F5-CS Item Examples I teach my child letter sounds. I try to make reading a fun time for my child. I make sure my child sees me reading. I am confident that my child will receive a good education. Compared to other children his/her age, my child is just as good or better at reading new words. I teach my child to read words. I let my child select the books when we read together. I read to myself. I am confident that my child will complete high school. Compared to other children his/her age, my child is just as good or better at identifying the sounds of letters. FELP Parental Beliefs (13 items) Parental Practices (32 items) Child Skill (6 items) α= .882 Expectations (7 items) α= .935 Skill Building (17 items) α= .918 Interactive Reading/Enjoyment (11 items) α= .922 Modeling & Monitoring (4 items) α= .676 Reliability Statistics Means, Std. deviation, Cronbach’s Alpha, Item Correlation FELP M(SD) α Item-total r F1 - Skill Building (17 items) 56.01 (13.57) .918 .208-.747 F2- Interactive Reading/Enjoyment (11 items) 40.63 (9.49) .922 .325-.777 F3- Expectations (7 items) 33.17 (3.21) .935 .504-.857 F4 - Child Skill (6 items) 21.85 (4.94) .882 .377-.772 F5 - Modeling & Monitoring (4 items) 12.34 (3.47) .676 .217-.532 Rasch Analysis Summary Statistics Item Response Pattern Person Factor Separation Reliability Real RMSE Model RMSE Mean Measure Skill Building 2.20 .87 .22 .20 .07 Interactive Reading/ Enjoyment 1.78 .84 .26 .24 .19 Modeling & Monitoring .47 .49 .31 .29 -.17 Expectations .63 .82 .38 .34 .69 Child Skill 2.20 .87 .22 .20 .07 Item Factor Separation Reliability Real RMSE Model RMSE Mean Measure Skill Building 4.06 .94 .48 .48 .37 Interactive Reading/ Enjoyment 4.16 .95 .54 .54 .46 Modeling & Monitoring 3.74 .93 .64 .64 .62 Expectations 4.68 .96 .59 .59 .59 Child Skill 4.06 .94 .48 .48 .37 -6 -4 -2 0 2 4 6 8 FELPQ33 FELPQ34 FELPQ35 FELPQ36 FELPQ37 FELPQ38 t-value Item English Other Child Skill - Language -6 -5 -4 -3 -2 -1 0 1 2 3 FELPQ39 FELPQ40 FELPQ41 FELPQ42 FELPQ43 FELPQ44 FELPQ45 t-value Item English Other Expectations - Language -6 -4 -2 0 2 4 6 8 10 FELPQ2 FELPQ6 FELPQ9 FELPQ10 FELPQ11 FELPQ13 FELPQ14 FELPQ15 FELPQ22 FELPQ27 FELPQ30 t-value Item English Other Interactive Reading/ Enjoyment - Language -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 FELPQ1 FELPQ16 FELPQ17 FELPQ25 t-value Item English Other Modeling and Monitoring - Language -4 -3 -2 -1 0 1 2 3 4 5 6 FELPQ3 FELPQ4 FELPQ5 FELPQ7 FELPQ8 FELPQ12 FELPQ18 FELPQ19 FELPQ20 FELPQ21 FELPQ23 FELPQ24 FELPQ26 FELPQ28 FELPQ29 FELPQ31 FELPQ32 t-value Item English Other Skill Building - Language RESULTS Structure Matrix a Factor 1-SB 2-IR 3-Ex 4-CS 5-MM FELPQ1 .352 FELPQ2 .676 FELPQ3 .445 FELPQ4 .633 FELPQ5 .694 FELPQ6 .753 FELPQ7 .667 FELPQ8 .414 FELPQ9 .618 FELPQ10 .656 FELPQ11 .856 FELPQ12 .590 FELPQ13 .752 FELPQ14 .847 FELPQ15 .849 FELPQ16 .774 FELPQ17 .569 FELPQ18 .688 FELPQ19 .738 FELPQ20 .776 FELPQ21 .670 FELPQ22 .507 FELPQ23 .653 FELPQ24 .677 FELPQ25 .642 FELPQ26 .560 FELPQ27 .649 FELPQ28 .596 FELPQ29 .564 FELPQ30 .676 FELPQ31 .601 FELPQ32 .620 FELPQ33 .604 FELPQ34 .776 FELPQ35 .834 FELPQ36 .824 FELPQ37 .649 FELPQ38 .763 FELPQ39 .758 FELPQ40 .805 FELPQ41 .874 FELPQ42 .885 FELPQ43 .826 FELPQ44 .776 FELPQ45 .813 Extraction Method: Principal Axis Factoring. Rotation Method: Oblimin with Kaiser Normalization. a. Imputation Number = 1 Factor Correlation Matrix a Factor 1-SB 2-IR 3-Ex 4-CS 5-MM 1-SB 1.000 .570 .138 .336 .340 2-IR .570 1.000 .169 .247 .488 3-Ex .138 .169 1.000 .295 .102 4-CS .336 .247 .295 1.000 .177 5-MM .340 .488 .102 .177 1.000 Extraction Method: Principal Axis Factoring. Rotation Method: Oblimin with Kaiser Normalization. a. Imputation Number = 1
Transcript of Measuring Family Early Literacy Practices Across Diverse ......measuring family early literacy...
ABSTRACT
The purpose of this presentation is to assess the psychometric properties of a self-report questionnaire measuring family early literacy practices (FELP). Rash analysis was conducted to evaluate item response patterns across diverse subgroups. Preliminary findings indicate the FELP is a reliable and valid measure for assessing family early literacy practices. Session attendees will learn about the validation of a self-report questionnaire. The benefits of analyzing item response patterns among diverse populations will be discussed.
INTRODUCTION
-Whitehurst and colleagues have found positive correlations and longitudinal stability between early literacy skills and later reading skills, which supports the need for early intervention (1999).
-Researchers have determined that indicators of a rich home environment include parent and guardians’ responsiveness to
their children’s early literacy abilities, involvement with their children in language and literacy-based activities and routines, and the provision of literacy materials (Hart & Risley, 1995; Roberts, Jurgens, & Burchinal, 2005).
-As children generally spend a large portion of time with their families, family involvement in literacy activities is strongly related to child achievement (Evans, 1998).
-Recent research has investigated the relationship between parental beliefs and behaviors regarding literacy and outcome
of their children (Meagher, Arnold, Doctoroff & Baker, 2008; Weigel, Martin, & Bennet, 2006).
-It has been hypothesized that these behaviors and expectations manifest as literacy promoting behaviors which benefit child learning (Goodnow & Collins, 1990; Roskos & Christie, 2000).
-The present study examines the psychometric properties of the family early literacy practices (FELP) questionnaire in a large and diverse sample of preschool age children from Jacksonville, Florida. The aim of the study is to answer the following questions:
1 ∙ Does the original factor structure of the FELP remain consistent for a large and diverse sample of
preschool-age children? 2 ∙ Do item response patterns differ among diverse subgroups (e.g. native versus non-native English speakers)?
DISCUSSION 1 ∙ Results indicate the FELP has good reliability and validity for parents of preschool age children. 2 ∙ Exploratory factor analysis of the FELP yielded support for a five-factor model, which aligned with the theoretical construct of the FELP. 3 ∙ Internal consistency of the FELP was satisfactory. However the reliability coefficient of the modeling and monitoring factor of the FELP was below acceptable limits (Cronbach’s alpha =
.67). This is not surprising given the fact that this FELP factor only consists of four items. 4 ∙ This study also provides support for the construct validity of the FELP for parents of preschool age children. Rasch analysis revealed that the threshold for four of the five factors
(exception was Modeling and Monitoring) was in the appropriate order. This means the thresholds increased in a positive direction as the category label increased. 5 ∙ The people mean measure for Expectations was the highest at .69, which is more than two-thirds of a standard deviation above the mean of the items. This demonstrates that
people typically endorsed many positive items for the Expectation factor, which ask parent’s about their beliefs about their children’s future education. The high mean measures for this scale suggest that most people positively endorsed those items. This finding is not surprising given that you might expect parents to believe positively about their children’s academic future.
6 ∙ Rasch analysis supported the reliability findings from the factor analysis. 7 ∙ Rasch analysis demonstrates that response patterns varied by primary language spoken in the home for all 5 factors.
Future Research: ◦ Include preschool age children who may not be attending a formal preschool setting in an effort to include a more diverse sample in future studies. ◦ Evaluate DIF between diverse subgroups. ◦ Conduct validity and reliability assessments of the FELP in Spanish with Spanish speaking families to investigate whether this measure translates to a Spanish speaking population. ◦ Compare the family measures to child outcome data with a diverse population.
References: Evans, M. (1998). Parental involvement in beginning reading: Preliminary report from a three year longitudinal study. Canadian Journal of School Psychology, 14(1), 11-20. Goodnow, J. J. & Collins, A. W. (1990). Development according to parents: The nature, sources, and consequences of parents' ideas. Hillsdale, NJ, England: Lawrence Erlbaum Associates, Inc. Hart, B., & Risley, T. R. (1980). In vivo language intervention: Unanticipated general effects. Journal of Applied Behavior Analysis,13(3), 407-432. Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47, 149 –74. Meagher, S. M., Arnold, D. H., Doctoroff, G. L., & Baker, C. N. (2008). The relationship between maternal beliefs and behavior during shared reading. Early Education and Development, Special Issue: Parent-Child
Interaction and Early Literacy Development, 19(1), 138-160. Roberts, J., Jurgens, J., & Burchinal, M. (2005). The role of home literacy practices in preschool children's language and emergent literacy skills. Journal of Speech, Language, and Hearing Research, 48(2), 345-
359. Roskos, K. A. & Christie, J. F. (2000). Play and literacy in early childhood: Research from multiple perspectives. Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers. Weigel, D. J., Martin, S. S., & Bennett, K. K., (2006). Contributions of the Home Literacy Environment to Preschool-Aged Children's Emerging Literacy and Language Skills. Early Child Development and Care, 176(3-
4), 357-378. Whitehurst, G. J., Zevenbergen, A. A., Crone, D. A., Schultz, M. D., Velting, O. N., & Fischel, J. E. (1999). Outcomes of an emergent literacy intervention from Head Start through second grade. Journal of
Educational Psychology, 91(2), 261-272.
METHOD Participants
• 2079 parents of preschool age children (48.6% female and 48.8% male) from a variety of educational preschool settings in Jacksonville, Florida. • Education: 43.7% Bachelors or higher, 49.7% HS or Some College, 5% No HS Diploma. • Income: 27.2% over $75K, 28.5% $40-74K, 37.4% under $40K. • Ethnicity: 53.1% White, 21.4% Black, 24.1% Other. • Language: 86.7% English, 11.2% Other. • Parents completed the FELP questionnaire. • Multiple imputation enabled all participant
information to remain. Instrumentation • The FELP is a research-developed questionnaire (Likert Scale).
• There are 5 factors: Skill Building, Interactive Reading/ Enjoyment, Modeling and Monitoring, Expectations, and Child Skill. • Parental Behaviors: Skill Building, Interactive Reading/ Enjoyment, and Modeling and Monitoring. • Parental Beliefs: Expectations and Child Skill.
• Exploratory Factor Analysis used to obtain factors (majority Caucasian middle-class families) revealed the FELP had 5 robust factors with adequate alpha coefficients ranging from .77 to .87.
Measuring Family Early Literacy Practices Across Diverse Preschool Families
Results
Data Entered Data Analyzed
Data Collected
Data Analysis -Exploratory factor analysis
• Examine the factor structure of the FELP.
-Reliability • Internal consistency
coefficients (Cronbach’s alphas) and item-total correlations of the total scale and subscales of the FELP.
-Rasch Analysis
• Examine the construct of the FELP.
• The Rating Scale Model (RSM), used to test the unidimensionality of each hypothesized factor (Andrich, 1978; Masters, 1982).
• DIF was used to evaluate the item response pattern among diverse subgroups. An acceptable range for the t value is between -2 to 2 (Bond & Fox, 2007).
FELP Questionnaire
Skill Building (n=10)
.92
.94 Expectations (n=7)
Child Skills (n=6)
Interactive Reading / Enjoyment (n=8)
.86
4
FELP Factor Structure Factor Loadings Factor Correlation Matrix
Dr. Laura Bailet, Dr. Suzanne Murphy, and Dr. Cynthia Zettler-Greeley
Nemours BrightStart! Dyslexia Initiative
Jacksonville, FL
Kandia Lewis and Dr. Marika Ginsburg-Block
University of Delaware Newark, DE
FELP Factor Structure
F1-SB F2-IR F3-MM F4- Ex F5-CS
Item Examples I teach my child letter sounds.
I try to make reading a fun time for my child.
I make sure my child sees me reading.
I am confident that my child will receive a good education.
Compared to other children his/her age, my child is just as good or better at reading new words.
I teach my child to read words.
I let my child select the books when we read together.
I read to myself. I am confident that my child will complete high school.
Compared to other children his/her age, my child is just as good or better at identifying the sounds of letters.
FELP
Parental Beliefs (13 items)
Parental Practices (32 items)
Child Skill (6 items) α= .882
Expectations (7 items) α= .935
Skill Building (17 items) α= .918
Interactive Reading/Enjoyment (11 items) α= .922
Modeling & Monitoring (4 items) α= .676
Reliability Statistics Means, Std. deviation, Cronbach’s
Alpha, Item Correlation FELP M(SD) α Item-total r
F1 - Skill Building
(17 items)
56.01 (13.57) .918 .208-.747
F2- Interactive Reading/Enjoyment
(11 items)
40.63 (9.49) .922 .325-.777
F3- Expectations
(7 items)
33.17 (3.21) .935 .504-.857
F4 - Child Skill
(6 items)
21.85 (4.94) .882 .377-.772
F5 - Modeling & Monitoring
(4 items)
12.34 (3.47) .676 .217-.532
Rasch Analysis Summary Statistics
Item Response Pattern
Person Factor Separation Reliability Real RMSE Model RMSE Mean Measure
Skill Building 2.20 .87 .22 .20 .07
Interactive Reading/ Enjoyment
1.78 .84 .26 .24 .19
Modeling & Monitoring .47 .49 .31 .29 -.17
Expectations .63 .82 .38 .34 .69
Child Skill 2.20 .87 .22 .20 .07
Item Factor Separation Reliability Real RMSE Model RMSE Mean Measure
Skill Building 4.06 .94 .48 .48 .37
Interactive Reading/ Enjoyment
4.16 .95 .54 .54 .46
Modeling & Monitoring 3.74 .93 .64 .64 .62
Expectations 4.68 .96 .59 .59 .59
Child Skill 4.06 .94 .48 .48 .37
-6
-4
-2
0
2
4
6
8
FE
LP
Q3
3
FE
LP
Q3
4
FE
LP
Q3
5
FE
LP
Q3
6
FE
LP
Q3
7
FE
LP
Q3
8
t-v
alu
e
Item
English
Other
Child Skill - Language
-6
-5
-4
-3
-2
-1
0
1
2
3
FE
LP
Q3
9
FE
LP
Q4
0
FE
LP
Q4
1
FE
LP
Q4
2
FE
LP
Q4
3
FE
LP
Q4
4
FE
LP
Q4
5
t-va
lue
Item
English
Other
Expectations - Language
-6
-4
-2
0
2
4
6
8
10
FE
LP
Q2
FE
LP
Q6
FE
LP
Q9
FE
LP
Q1
0
FE
LP
Q1
1
FE
LP
Q1
3
FE
LP
Q1
4
FE
LP
Q1
5
FE
LP
Q2
2
FE
LP
Q2
7
FE
LP
Q3
0
t-va
lue
Item
English
Other
Interactive Reading/ Enjoyment - Language
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
FE
LP
Q1
FE
LP
Q1
6
FE
LP
Q1
7
FE
LP
Q2
5
t-va
lue
Item
English
Other
Modeling and Monitoring - Language
-4
-3
-2
-1
0
1
2
3
4
5
6
FE
LP
Q3
FE
LP
Q4
FE
LP
Q5
FE
LP
Q7
FE
LP
Q8
FE
LP
Q1
2
FE
LP
Q1
8
FE
LP
Q1
9
FE
LP
Q2
0
FE
LP
Q2
1
FE
LP
Q2
3
FE
LP
Q2
4
FE
LP
Q2
6
FE
LP
Q2
8
FE
LP
Q2
9
FE
LP
Q3
1
FE
LP
Q3
2
t-va
lue
Item
English
Other
Skill Building - Language
RESULTS
Structure Matrixa
Factor
1-SB 2-IR 3-Ex 4-CS 5-MM
FELPQ1 .352
FELPQ2 .676
FELPQ3 .445
FELPQ4 .633
FELPQ5 .694
FELPQ6 .753
FELPQ7 .667
FELPQ8 .414
FELPQ9 .618
FELPQ10 .656
FELPQ11 .856
FELPQ12 .590
FELPQ13 .752
FELPQ14 .847
FELPQ15 .849
FELPQ16 .774
FELPQ17 .569
FELPQ18 .688
FELPQ19 .738
FELPQ20 .776
FELPQ21 .670
FELPQ22 .507
FELPQ23 .653
FELPQ24 .677
FELPQ25 .642
FELPQ26 .560
FELPQ27 .649
FELPQ28 .596
FELPQ29 .564
FELPQ30 .676
FELPQ31 .601
FELPQ32 .620
FELPQ33 .604
FELPQ34 .776
FELPQ35 .834
FELPQ36 .824
FELPQ37 .649
FELPQ38 .763
FELPQ39 .758
FELPQ40 .805
FELPQ41 .874
FELPQ42 .885
FELPQ43 .826
FELPQ44 .776
FELPQ45 .813
Extraction Method: Principal Axis Factoring.
Rotation Method: Oblimin with Kaiser Normalization.
a. Imputation Number = 1
Factor Correlation Matrixa
Factor 1-SB 2-IR 3-Ex 4-CS 5-MM 1-SB 1.000 .570 .138 .336 .340
2-IR .570 1.000 .169 .247 .488
3-Ex .138 .169 1.000 .295 .102
4-CS .336 .247 .295 1.000 .177
5-MM .340 .488 .102 .177 1.000
Extraction Method: Principal Axis Factoring.
Rotation Method: Oblimin with Kaiser Normalization.
a. Imputation Number = 1
