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### 108 Cards in this Set

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 Definition: Range (Largest variable) - (Smallest variable) Definition: Variance The spread of the variables in the distribution Definition: Standard Deviation The square root of the variance. Normal distribution: % of variables in the distribution one standard deviation above and below the mean. 68% Normal distribution: % of variables in the distribution two standard deviations above and below the mean. 95% Normal distribution: % of variables in the distribution three standard deviations above and below the mean. 99% Definition: Z-score The number of standard deviations above a mean where a variable lies. Definition: Percentile # of variables at or below that level. Definition: Interquartile range The range of values between the 25th and 75th percentile. Definition: Left skewed distribution Tail on left. Mode on right. Defintion: Right skewed distribution Tail on right. Mode on left. Definition: T-distribution Different distribution for each sample size Central limit theorem Given a sufficiently large sample size, a sample drawn from the population will be normally distributed regardless of the shape of the original population distribution. Definitions: Standard Error of the Mean (descriptive and mathematical definitions) Descriptive: Variability in a distribution of sample means Which is larger: standard error the mean OR standard deviation standard deviation Definition: 95% confidence interval the interval such that the true value has a 95% probability of lying within Definition: P-value Given the null hypothesis is true, the probability off getting a result as extreme or more extreme than the observed outcome by chance alone. Definition: Alpha value The value used to compare the p-value to to determine if it is significant. P-value > Alpha value: Conclusion? Results are likely due to chance alone and are not statistically significant. P-value <= Alpha value Results are unlikely due to chance alone and are statistically significant. Definition: Null hypothesis There is no difference between the groups being assessed. Definition: Alternative hypothesis There is a difference bbetween the two groups being assessed. Definition: Two-tailed alternative hypothesis The two groups' values are not equal. (no more specific than that) Definition: One-tailed alternative hypothesis One groups' values is less than those of the other group Definition: Type 1 (Alpha) Error Incorrectly rejecting the null hypothesis ( a false positive conclusion) Definition: Type 2 (Beta) Error Failure to reject the null hypothesis when the alternative hypothesis is correct (a false negative conclusion) Definition: Power The probability of finding a specified difference, or larger, when a true difference exists The difference between statistical significance and clinical significance Statistical significance only comments on chance, not benefit to patient. Generally, minimum power for a clinically relevant difference 80% or more Problem with performing multiple tests without adjusting error Increases probability of a Type 1 error. Bonferroni correction Divide alpha by number of statistical tests to perform to yield a new alpha. The name for the type of correction where alpha is divided by the number of statistical tests to perform. Bonferroni Correction Difference between parametric and non-parametric tests Parametric: performed on data that are normally distributed Chi-square test Performed on discrete data Fisher's exact test Performed on discrete data The other name for the Student t-test two sample t-test The other name for the two sample t-test Student t-test Student t-test/Two sample t-test Performed on normally distributed data One sample t-test Performed on normally distributed data What does ANOVA stand for? ANalysis ANOVA Performed on normally distributed data Paired t-test Performed on normally distributed data Correlation Performed on normally distributed data Pearson's Correlation coefficient aka rho Rho aka Pearson's Correlation coefficient Spearman Rank Correlation Performed on non-normally distributed data R-squared aka Coefficient of determination Coefficient of Determination aka R-squared Multiple regression analysis Has two or more independent variables Logistic regression analysis Performed when the dependant variable is binary Primary screening Peformed to prevent a disease Secondary screening Peformed to reduce the impact of a disease Sensitivity Given disease is present, the probability of testing positive Specificity Given disease is absent, the probability of testing negative Predictive value positive Given the test is positive, the probability that the disease is present Predictive value negative Given the test is negative, the probability disease is absent Types of descriptive studies Case Report Difference between a case report and a case series One versus multiple interesting observations Correlation study Descriptive study done on large populations (the per capita meat consumption of a town and the prevalance of CAD there) Prevalance study aka Cross-Sectional study Stratified Random Sample Sample is first stratified into groups, and then subjects are tne randomly drawn from each group. Types of analytic studies and how their subjects are selected Case Control (Outcome, then exposure is assessed) Randomized Controlled Trial: Pros gold-standard Randomized Controlled Trial: Cons May take time = \$ and loss-to-follow-up of subjects Prospective Cohort Study: Pros generates incidence data Prospective Cohort Study: Cons bad for rare outcomes Retrospective Cohort Study: Pros easy to do, so less \$ Retrospective Cohort Study: Cons bad for rare outcomes Case Control: Pros good for rare disease Case Control: Cons subject to several biases as recall bias, interview bias, selection bias Meta-analysis: Pros increases power by combining study results Meta-analysis: Cons Studies not done exactly the same way Difference between intention-to-treat analysis and efficacy analysis, and which is prefered by the FDA Intention to treat: All subjects analyzed by study arm, regardless of compliance Phase One Study Safety Phase Two Study Efficacy Phase Three Study Compares new treatment to standard therapy Prevalance The proportion of subjects in a group with a certain disease, includes new and old cases (a snapshot in time) Incidence New cases occurring over a defined period of time Cumulative Incidence aka Attack Rate Attack Rate aka Cumulative Incidence Incidence Rate aka Density Density aka Incidence Rate Relationship of Prevalence to Incidence Rate Prevalence = (Incidence Rate)(Average Duration of Disease) Absolute Risk The probability of going from a healthy state to an ill state (eg the probability that person x will develop condition y over the next z years when they don't have it already) Relative Risk The strength of association between an exposure and outcome. (xy): x: exposure, y: disease 0=negative, 1=positive Relative Risk (calculated from prevalances) Relative Risk = Prevalence of disease in population A divided by Prevalence of disease in population B Odds Ratio An approximation of relative risk used in case control studies. (xy): x: exposure, y: disease 0=negative, 1=positive Attributable Risk Excess disease in the exposed population that can be attributed to the exposure (xy): x: exposure, y: disease 0=negative, 1=positive Confounding An erroneous study conclusion when a factor is associated with an exposure and is itself an independent risk factor for the outcome Ways to control for confounding Restriction (subjects with known risk factors are excluded) Effect Modification aka Interaction Surveillance Bias One cohort is followed more closely than another and is thus more likely to be diagnosed with the disease, leading to a difference in risk estimation between the two cohorts Interaction aka Effect Modification Herd immunity Disease protection of an unimmunized individual because the population is immunized Epidemic curve Plots an epidemic by: Kaplan Meier survival cuves Shows survival of different groups over time. Bias A systematic error with a study leading to an erroneous estimation of the association between the exposure and the outcome 4 major types of bias -Recall bias (differential recall of exposure status by individuals based on their health status) Criteria for cause-effect relationships -Strength of association (how large or small is the relative risk/odds ratio Definition: Epidemic Greater than expected disease frequency in a defined population Definition: Pandemic Greater than expected disease frequency in a large defined area Definition: Endemic Constant presence of a disease in a defined population Case Fatality Rate Proportion of patients with a disease who die of that disease Mortality Rate Proportion of patients who die of a disease in a defined population Key difference between Case Fatality rate and Mortality Rate The denominator: