ClinEpi Review

Clinical Epidemiology made really, really simple.

ClinEpi Review is an introductory level course on clinical epidemiology that explains the most commonly encountered terms and concepts in health research and evidence-based medicine. This course was designed for all healthcare professionals seeking to better understand health research and practice evidence-based medicine. ClinEpi Review consists of 15 videos on a variety of topics each ranging from 3 to 13 minutes in duration for a total duration of just under 2 hours and 20 minutes.

The video series also includes a downloadable workbook and answer key based on the content of the videos.

$150.00Add to cart

Episodes

00 Introduction (FREE) 2:41 Welcome and Introduction to the series.
01 Definitions 6:57 An explanation of cohorts, prevalence & incidence and how to calculate the latter two.
02 Variables 5:15 An explanation of independent, dependent & confounding variables and how they relate to one another.
03 Observational Studies 8:59 An explanation of the features, strengths and limitations of the following observational study designs: case & case series studies, cross-sectional study, ecologic study, cohort study, & case-control study.
04 Randomized Controlled Trials 11:07 An explanation of the features, strengths & variations (parallel, cross-over, cluster, factorial) of RCTs as well as some of the commonly associated biases. Also, an explanation of methods of data analysis, missing data and the CONSORT Statement.
05 Two by Two Tables Tables 2:59 An explanation of the two by two table, the foundation on which many calculations in clinical epidemiology are performed including but not limited to relative risk, absolute risk reduction (& increase), relative risk reduction, number needed to treat (& harm), predictive value, sensitivity & specificity.
06 All About Risk 7:17 An explanation of risk, event rate, absolute risk reduction (& increase), number needed to treat (& harm) & relative risk reduction as well as how to calculate each.
07 Risk & Odds 10:30 An explanation of risk & odds, specifically relative risk (risk ratio) and odds ratio how to calculate each and their differences.
08 Predictive Values, Sensitivity and Specificity 8:43 An explanation of positive predictive value, negative predictive value, sensitivity & specificity, their strengths, weaknesses, similarities, differences, clinical applications & how they are each calculated.
09 ROC Curves 6:09 An explanation of the Receiver Operating Characteristic (ROC) Curve and how it relates to sensitivity & specificity.
10 Likelihood Ratios 11:35 An explanation of likelihood ratios as diagnostic performance measures, their relationship to sensitivity & specificity and how each is calculated.
11 Data & Distribution 9:50 An explanation of categorical & quantitative data, data distribution, central tendency (mean, median, mode) range and variability (standard deviation & interquartile range).
12 Hypothesis Testing and Errors 9:13 An explanation of null and alternate hypotheses, P-value, alpha, beta, type I & II errors & power and how each is related to the others.
13 Point Estimates & Confidence intervals 6:15 An explanation of point estimates, interval estimates, confidence interval, confidence level, precision and how they relate to each other.
14 Which Test to Use 10:34 An explanation of parametric and nonparametric statistics, some of the more commonly used biostatistical tests (Chi-square test, McNemar’s test, Student’s T-test, Mann-Whitney U-test, analysis of variance [ANOVA], Kruskall-Wallis, linear regression, Spearman rank correlation), the parameters of each & examples of when each is typically applied.
15 Systematic Reviews 12:54 An explanation of systematic & non-systematic reviews, their differences as well as biases associated with the former.
16 Meta-analyses 9:46 An explanation of meta-analyses, how they relate to systematic reviews & heterogeneity in the pooling of results of meta-analyses.