Biostatistics Final Exam Definitions UTA
well answered to pass
Bonferroni-Holm Multiple Comparisons - correct answer ✔✔-In the context of an ANOVA, rejecting the
null hypothesis means there is a statistical difference between at least two means, but it won't tell you
where it is. You use this to discover exactly which means are different.
-Only used for Model I ANOVAs
-A t-statistic for a two sample t-test assuming equal variance
Steps to Applying the Bonferroni-Holm Multiple Comparison Test - correct answer ✔✔Step 1: Calculate
test statistics and corresponding P values for each of the m comparisons
Step 2: Order the P values from smallest to largest: p1,p2,...,pm. Label the corresponding comparisons:
C1,C2,...Cm
Step 3: Compare p1 and alpha(a)/m
(a) If p1 > a/m, then stop. Conclude that there is no evidence of differences between any of the means.
Procedure is done
(b) p1 < or = a/m, then reject Ho for C1. Continue to next step.
Step 4: Compare p2 and a/(m-1)
(a) If p2 > a/(m-1), then stop. There is no evidence of differences between any of the means in the
remaining comparisons. Procedure is done.
(b) p2 < or = a/(m-1), then reject Ho for C2. Continue to next step.
Step 5: Compare p3 and a/(m-2)
, (a) If p3 > a/(m-2), then stop. There is no evidence of differences between any of the means in the
remaining comparisons. Procedure is done.
(b) p3 < or = a/(m-2), then reject Ho for C3. Continue to next step
Continue until procedure requires you to stop or until all P values have been compared
Kruskal-Wallis Test - correct answer ✔✔The nonparametric analog to a Model I One-Way ANOVA. We
would use if it we reject the assumption of normality for the data.
Randomized-Complete Block Design ANOVA - correct answer ✔✔Used to extend paired experimental
designs to accommodate making more than just two measurements on the same individuals. Also called
Repeated Measures ANOVA.
Model Assumptions:
1. Each observation constitutes a random, independent sample from a population with mean u_ij. There
are k x b of these populations sampled.
2. Each of the k x b populations is normal and with the same variance.
3. The treatment and block effects are additive, that is, there is no interaction (synergy or interference)
between blocks and treatments.
1. The observations in each cell constitute an independent random sample of size n from a population
with mean u_ij
2. Each of the population represented by the cell samples is normal and has the same variance.
Friedman k-sample Test: Matched Data - correct answer ✔✔The nonparametric analog to the
Randomized-Complete Block Design ANOVA
Linear Regression - correct answer ✔✔Examines the amount of variability in one variable (Y) that is
explained by the changes in another variable (X). Typically used in situations in which we have control of
X and can measure it essentially without error.
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