Sections View Full Chapter Figures Tables Videos Annotate Full Chapter Figures Tables Videos Supplementary Content + TEST TAKING TIPS Download Section PDF Listen +++ ++ Test Taking Tips Memorize the table below for easy calculation of sensitivity, specificity, and positive and negative predictive values. Know the differences between different types of statistical tests. ++ +++ What is sensitivity? ++ Proportion of truly diseased persons in a screened population who are identified as being diseased by the test. It is a measure of the probability of correctly diagnosing a condition. +++ Sensitivity equation: ++ True positive/(true positive + false negative) +++ What is specificity? ++ The proportion of truly nondiseased persons who are so identified by the screening test +++ Specificity equation: ++ True negative/(false positive + true negative) +++ False-positive rate: ++ 1 – specificity +++ False-negative rate ++ 1 – sensitivity +++ What is positive predictive value? ++ The probability that a person with a positive test result has the disease +++ What is the positive predictive equation? ++ True positive/(true positive + false positive) +++ What is the negative predicted value? ++ The probability that a patient with a negative test result really is free of the disease +++ What is the negative predicted value equation? ++ True negative/(false negative + true negative) +++ Definition of prevalence: ++ The total number of cases of a given disease in a specified population at a designated time +++ Definition of incidence: ++ The number of new cases of a given disease during a given period in a specified population +++ What is the absolute risk reduction? ++ The absolute arithmetic difference in outcome rates between control and experimental patients in a trial +++ What is relative risk reduction? ++ The proportional reduction in outcome rates between control and experimental patients in a trial +++ A range of values that has a specified probability of containing the rate or trend: ++ Confidence intervals +++ A method of studying a drug or procedure in which both the subjects and investigators are kept unaware of who is actually getting which specific treatment: ++ Double-blind method +++ The number of patients who need to be treated to prevent one adverse outcome: ++ Number Needed To Treat +++ The probability that an event will occur: ++ Risk +++ The number of units in a population to be studied: ++ Sample size +++ The number of deaths during a specific time period: ++ Mortality +++ The proportion of patients alive at some point after the diagnosis: ++ Survival +++ What is the null hypothesis? ++ Denoted by Ho; it is a proposal that there is no difference in a comparison. +++ What is a Type I error? ++ Rejecting the null hypothesis tested when it is true (α) +++ What is a Type II error? ++ Failing to reject the null hypothesis when a given alternative hypothesis was true (β) +++ The probability that the test will reject the hypothesis tested when a specific alternative hypothesis is true: ++ Power (1 – β) +++ Sum of all results divided by the number of results: ++ Mean +++ The middle value that divides the distribution of data: ++ Median +++ The most common value in data set: ++ Mode +++ The extent to which a test measures what it claims to measure: ++ Validity +++ The consistency with which the data collection process measures whatever it measures: ++ Reliability +++ An estimate of the population mean is: ++ Sample mean +++ What is central limit theorem? ++ For a large enough sample size n, the distribution of the sample mean will approach a normal distribution +++ What is standard deviation (SD)? ++ It is a predictable measure of dispersion from the mean in a Gaussian normal distribution +++ What is the square root of the variance? ++ SD +++ What are case-control studies? ++ Observational retrospective study to study risk factors and causation for desired/predefined cases (outcome). Good for rare diseases. For example, comparing smoking history of acute myocardial infarction (MI) (cases) patient versus smoking history of patient without MI (control) +++ What are prospective cohort studies? ++ Observational study of treatment outcome for patient groups that could not be randomized (cohorts) for ethical reasons. For example, following long-term weight loss outcome of patients who received roux-en-y gastric bypass versus sleeve gastrectomy +++ What are retrospective cohort studies? ++ Differ from prospective cohort studies in that the exposure in question being studied are collected retrospectively For example, studying if certain preprocedural comorbidities will affect the long-term weight loss outcome of patients who received roux-en-y gastric bypass versus sleeve gastrectomy +++ What are randomized controlled trials? ++ Randomly selecting subjects to be allocated into treatment versus control group. Best design, minimizes biases +++ What are the different levels of evidences? ++ Level I: Evidence from at least 1 randomized controlled trial Level II-1: Evidence from well-designed controlled trial without randomization Level II-2: Evidence from well-designed cohort or case control studies Level II-3: Evidence from multiple time series with or without the treatment, or dramatic result in uncontrolled trials Level III: Expert opinion, clinical experience +++ What are t tests used for? ++ To assess statistical difference between sample means of the testing group versus known population mean (1-sample t test) or sample means of 2 independent or dependent groups (2-sample t test) for continuous variables +++ What is a paired t test? ++ A specific t test to compare 2 sample groups that are not randomly selected. For example, the second sample group is the first sample group after treatment. +++ What are Z tests? ++ Similar to t test, however, is used when sample size is greater than 30 (t test is for a limited sample size, ie, less than 30) and when SDs of the population are known +++ What is ANOVA? ++ Analysis of variance. It is used to determine whether there is a difference between the means of several different groups (as opposed to t tests, which only compare 2 groups). +++ What is χ2 test? ++ It tests whether the distribution of multiple categorical variables in the experimented population differs from the control. For example, proportion of surviving and nonsurviving cancer patients in 5 years after chemotherapy versus proportion of surviving and nonsurviving cancer patients without treatment. +++ What is Fisher exact test? ++ Similar to χ2 test, but specifically only compares 2 categorical variables