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We know of only one other study [15] that compared different PCR protocols (including those we examine here); while this was a valuable addition to the literature, their analysis assessed only agreement between tests and did not assess sensitivity or specificity, or indeed make estimates of the true prevalence based on the outcomes of the different tests.
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The choice is not between imposing graduation tests and doing nothing to improve education.
Finally, gender dummies and interactions between gender and APC groups were tested and did not yield substantively different results.
As anticipated, subjects in Group A, and Group C demonstrated immediate gains in knowledge (Test-r) following their participation in the educational program PC, while subjects in Group B received no education between Test-1 and Test-r, and did not show a similar increase.
The overall drop-out rate between tests done and post-HIV-test counselled was 5.3%, and that for HIV positive women was somewhat higher at 6.4% (Table 1).
We also performed pairwise Kolmogorov-Smirnov tests between each arrangement and did not detect any significant differences in the distribution of average Fop values for any comparison.
We sought a method to reduce this glucose bias without increasing the between-subject or test-retest variability and did this by considering that tissue glucose transport is a saturable yet unsaturated process best described as a nonlinear function of glucose levels.
Among the 3,275 individuals with complete data, we tested differences between patients who did and did not develop diabetes with χ tests for categorical variables and t tests or Kruskal-Wallis tests for normally or nonnormally distributed continuous variables.
The light intensity between test flasks did not vary in excess of ±15%%.
Comparisons of accuracies between tests were done using McNemar's test.
Comparisons between tests were done by the Student's t test.
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