Haves, Halves, and Have-Nots: School Libraries and Student Achievement in California Page: 155
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single factor for library variables consisting of total services, total technology, total staff hours,
and hours open.
The library factor accounted for 70.57% of the variance. See Table 56 for the factor matrix.
Component Matrix for Factor Analysis of Library Variables, Grade 8 Social Studies
Variable Factor 1a
Hours Open .82
Total Staff Hours .83
Total Services .85
Total Technology .87
Note: Extraction method was principal component analysis.
a. Only one component was extracted.
The school and community factors were then entered into the first step of a hierarchical
multiple regression, followed by the library factor added in the second step. Assumptions of
linearity, normality and multicollinearity were met in tests outlined in the previous chapter.
Together, the school, community and library factors produced an adjusted R2 of .60 (F(3, 1141)
574.16,p <.001) for the prediction of eighth grade Social Studies CST scores. Consistent with
the other eighth grade regression, Beta weights indicated that the strongest predictor was the
community factor (-.70), followed by school (.24) and library factors(. 17). The library factor
produced a AR2 of .03, meaning that it accounted for 3% of the variance in 8th grade Social
Studies CST scores. See Table 57 for unstandardized and standardized betas and standard error.
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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/m1/169/: accessed April 29, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .