Course Description
Basic statistical methods and analysis used to critically evaluate drug literature are discussed. Topics include statistical inference and hypothesis testing, selection of appropriate statistical tests, correlation and regression analysis, and research design. Students will apply these topics while evaluating published clinical trials, outcome studies, and materials from pharmaceutical manufacturers.
Athena Title
Stat Approach to Drug Lit Eval
Prerequisite
PHRM 3940
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
Upon completion of this course, students should be able to: Apply the concept of generalizability to research findings. Know the basic steps of scientific inquiry. Use and interpret basic biostatistical tools. Understand the concepts of statistical inference and hypothesis testing and apply these to the interpretation of drug literature. Know the components of clinical drug study design and how they affect choice and interpretation of statistical tests. Apply statistical knowledge and skills to interpret the usefulness of clinical drug studies, outcomes studies, and pharmaceutical company promotional materials commonly seen by the practicing pharmacist.
Topical Outline
1.Introduction to Research Inquiry - Concept of Generalizability to research findings - Basics steps to Scientific Inquiry 2. Review of Your First Statistics Course - Population and Samples - Nominal, Ordinal, Interval and Ratio Measures - Histograms, Box and Whisker Plots, and Bar Charts - Mean, mode, and median - Range, variance, and standard deviation - Principles of the central limit theorem and the standard error of the mean - Examples of these in drug literature 3. Statistical Inference and Hypothesis Testing - Study hypothesis, null hypothesis, and alternate hypothesis - Type-1 and Type II Errors and their relationship to alpha error, beta error, power, and p-value. - Examples of these in drug literature 4. Student t-test - Utilize a t-test to accept or reject hypotheses. - Utilize a Confidence interval to accept or reject hypotheses. - Utilize the two sample unpaired t-test to test hypotheses. - Know the assumptions underlying the t-test. - Examples of appropriate and inappropriate use in the drug literature 5. Contingency tables and categorical data analysis - Setting up a contingency data with categorical data - Calculating sensitivity and specificity of a diagnostic test - Interpreting sensitivity, specificity, false positive, and false negative rates - Calculating and interpreting measures of relative risk - Calculating and interpreting incidence and prevalence - Calculating the Chi-Square - Using the Chi-Square to test for differences - Assumptions and limitation of the Chi-Square - Examples from the drug literature 6. Correlation and Regression Analysis - Calculating and interpreting correlation coefficients - Utilizing correlations to identify significant associations - Examples of use in the drug literature 7. Research Design and Medical Literature Evaluation - Prospective, Cross Sectional, and Retrospective Designs - Design Features of the Randomized Controlled trial - Cohort and Case Control Studies - Potential biases in medical research - Validity and generalizability 8. Practical application - Clinical drug study evaluation - Outcomes study evaluation - Pharmaceutical company material evaluation