Mathematics Anxiety and Mathematics Self-efficacy in Relation to Medication Calculation Performance in Nurses Page: 85
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research should be done to standardize medication administration tests and fine tune
All variables were examined for missing data prior to conducting any analysis. The
missing data accounted for less than 5% of the data. There were no missing data in the MAS or
NSE-math items, so no recoding was done to these. Recoding was to be done using the neutral
score (3) for the MAS item missing, the "some confidence" score (5) for any NSE-math items
missing, and a zero (0) for a BB item not answered. The most common items left blank were IV
calculations. Missing data in the demographics were coded the same as the majority for nominal
data and the average for the interval or ratio data. Since nearly 92% reported Caucasian or White
and 4.7 % did not say, two categories, Caucasian and Other were coded.
Descriptive statistics were calculated and examined for determining basic distributional
assumptions. The distributional assumptions of reasonably normal distributions, linearly related,
and homoscedasticity using inspection of residuals were done as planned before statistical
analysis was completed (Erdfelder, 2010; Foster et al., 2006). Field (2009) detailed several
criteria about how to check the assumptions: The variable types have to be quantitative or at least
have two categories, the predictors have to have some variation and not be zero, no perfect linear
relationships between two or more predictors, and homoscedasticity checked by examining the
residuals at each level of predictor should have same variance. Data met assumption of
normalcy, linearity, and homoscedasticity and were deemed to be appropriate for analysis as
The variables at minimum have two quantifiable categories; for instance, gender has two
categories. All variables were coded to, at minimum, have two categories, and the major
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Melius, Joyce. Mathematics Anxiety and Mathematics Self-efficacy in Relation to Medication Calculation Performance in Nurses, dissertation, May 2012; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc115119/m1/93/: accessed January 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .