Haves, Halves, and Have-Nots: School Libraries and Student Achievement in California Page: 148
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varimax rotation. This procedure was also used to identify variables that correlated highly with
one another and formed factors (Leech, Barrett, & Morgan, 2005). Only factor loadings greater
than .600 were considered for inclusion in groupings, and only groupings with an eigenvalue of
at least 1 were retained. After rotation, the first factor accounted for 53.8% of the variance; the
second factor accounted for 17.8%, for a total of 71.6%. Table 49 displays the items and factor
loadings for the rotated factors, with loadings less than .40 omitted for clarity.
Component Matrix for Factor Analysis of School and Community Variables, Grade 4
Variable Factor 1 Factor 2
Average Parent Education .843
Free and Reduced Lunch -.910
Percentage English Learners -.910
Average Teacher Salary .817
Percent Teachers Fully Credentialed .641
Note: Extraction method was principal component analysis. Rotation Method: Varimax with Kaiser Normalization.
Rotation converged in 3 iterations.
Although percentage of English Learners is part of factor 1, this factor largely represents
community factors, while factor 2, average teacher salary and percent of teachers fully
credentialed, represents school factors.
A similar procedure was used to combine library variables. In the first factoring, budget
and collection size were eliminated for not loading at .600; all remaining variables loaded on a
single factor accounting for just 55.98% of the variance. Hours open was dropped as it had the
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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/m1/162/: accessed August 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .