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Task analyses included only patients attempting a given stage; numbers passing were analyzed with χ tests and pass rates for each stage with likelihood ratio analysis (38).
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The reads that passed were analyzed by miRDeep algorithm to predict novel miRNAs [18], [19].
Since the only drug samples (in testable form) to fail testing were fake copies of Viagra® containing zero active pharmaceutical ingredient (API), the prices of the drugs that failed and those that passed were analyzed, as well as the prices of those that were copies of Viagra®, which had active ingredient but would "fail" spectrometry testing.
The conventional clinical response outcomes at week 8 (that is, partial remission, BASDAI50, ASAS20 and ASAS40 responses, and PASS) were analyzed using a logistic regression model, including treatment and the corresponding baseline scores as covariates.
The effect of method on the number of bat passes was analyzed using a bootstrapped generalized linear mixed effect model.
The situations when the tests are not passed are analyzed and classified, and corresponding modifications for the first stage model are provided.
Therefore, each satellite pass was analyzed to identify and exclude unreliable data, which is often characterized by a double population of points in either the ion drift data or T ion data, or by large ion temperatures (T ion > 5000 K).
The coefficient of friction (COF) behavior and damage mechanism in the multi-pass scratches were analyzed.
Descriptive statistics and comparisons (using chi-square and t-tests) among programs with <100% and 100% pass rates were analyzed from 2009-2011.
Comparative pain, disability, rate of recovery and patient acceptable symptom state (PASS) measures were analyzed on the 68 subjects seen over an average of 56.1 days (standard deviation (SD)=55.4).
Data with the initially modified pass scores were analyzed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com