Haves, Halves, and Have-Nots: School Libraries and Student Achievement in California Page: 154
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factor, which will be called "Community factor," accounted for 61.82% of the variance, while
the second factor, called "school factor," accounted for 20.69% of the variance. See Table 55 for
the factor matrix.
Rotated Component Matrix for Factor Analysis of School and Community Variables, Grade 8
English Language Arts
Variable Factor 1 Factor 2
Average Parent Education -.83 .18
Free and Reduced Lunch .893 -.22
Ethnicity -.88 -.09
Percentage English Learners .88 .06
Average Teacher Salary -.05 .98
Note: Extraction method was principal component analysis. Rotation Method: Varimax with Kaiser Normalization.
Rotation converged in 3 iterations.
The first factor analysis for library variables resulted in the creation of two factors with an
Eigenvalue of greater than 1; however, the total variance of those two factors was just 54.31%.
Because collection size had the lowest extraction commonality-the amount of the variance in
the variable accounted for by the components-as well as the lowest rotated loading factor, this
variable was eliminated next. Removing collection size resulted in two factors that accounted
for just 59% of the variance. Budget total was eliminated next because it loaded most weakly and
had the lowest extraction communality among remaining variables. Remaining variables loaded
on a single factor; the loading value for average copyright was .18; this was removed for a final,
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Achterman, Douglas L. Haves, Halves, and Have-Nots: School Libraries and Student Achievement in California, dissertation, December 2008; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc9800/m1/168/: accessed January 24, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .