Statistical AnalysisDescriptive sta

Statistical Analysis
Descriptive statistics, including means, standard deviations,
and frequencies,were used to describe nurses’
characteristics asmeasured by the included RN4CAST
nurse survey items. The hypothesized model was evaluated
using path analysis (Figure 2), which allowed
the identification of direct and indirect relationships
between observed variables.24 Model fit was assessed
using both comparative fit index (CFI) and Tucker-
Lewis index (TLI),with values close to 0.95 as comparative
(incremental) fit measures, and root-mean-square
error approximation (RMSEA) less than 0.06 as a
parsimony-adjusted fit measure.25 The modification
indices and standardized residual covariances were
also examined to evaluate model fit, to indicate misspecification
of our hypothesized model and to guide
model modification. We used maximum likelihood
estimation with missing values, which is equivalent to
imputation using full information maximum likelihood.
26 Descriptive statistics were computed using
IBM SPSS 20 (IBM Inc, Armonk, New York), with
STATA 12.1 (StataCorp LP, College Station, Texas)