Final Exam Flashcards
Efficacy
The extent to which a specific intervention, procedure, regimen, or service produces beneficial results under IDEAL CONDITIONS.
Effectiveness
A measure of the extent to which a specific intervention, procedure, regimen, or service, when deployed in the field in ROUTINE CIRCUMSTANCES, does what it is intended to do for a specified population.
Hierarchy of Evidence Quality
1) Systemic Reviews and Meta-Analysis
2) Clinical Trials (in humans)
3) Longitudinal Cohort Studies
4) Case-Control Studies
5) Descriptive and Cross-Sectional Studies
6) Case reports and Case series
7) Personal opinion, subjective impressions, anecdotal accounts
Impact Factor
Total number of citations to articles appearing in that journal/ Total number of articles published
Three types of papers published in journals
1) Research Reports
2) Reviews of literature to summarize knowledge in a particular area
3) Commentaries
Components of a Research Report
1) Title
2) Author
3) Date of submission and acceptance
4) Abstract or Summary
5) Introduction
6) Materials and Methods
7) Results
8) Discussion
9) Conclusion
Scales of Measurement (3)
1) Nominal
2) Ordinal
3) Continuous
- Interval
- Ratio
Measures of Central Tendency
1) Mode
2) Median
3) Mean
Measures of Variability
1) Range
2) Interquartile Range
3) Variance
4) Standard Deviation
5) Coefficient of Variation
6) Standard error of the Mean
Standard Deviation
Used to measure variability of Individual subjects around a sample mean
Standard Error
Used to assess how accurately a sample mean reflects a population mean
Central Limit Theorem
In random samples of N observations, sample means will be normally distributed.
significance: allows us to make inference about the population from which our samples are drawn.
Confidence interval for a mean
Lower confidence bound and an upper confidence bound with the population mean contained within this interval (1-alpha) percent of the time.
For normal and t distributions, the confidence interval is centered around the mean. Confidence intervals get larger as you decrease the amount of error.
Research Hypothesis
Prediction based on the theory being tested on preliminary observations; on concentrations or guesses. (ex: gender affects intelligence)
Null Hypothesis
A mathematical statement, usually in population parameters, of no difference. Can be directional or non-directional.
Alternative Hypothesis
An objective hypothetical statement of the research hypothesis similar to the null hypothesis. We PROVE the alternative hypothesis by showing that the null hypothesis is not true.
Type I Error
Probability associated with rejecting the null hypothesis when it is true. (saying there are effects when there are none) ex: saying males are smarter than females when they are not.
Type II Error
The probability associated with accepting the null hypothesis when it is actually false. (saying there are no effects when there actually are)`
Power
The probability of rejecting the null hypothesis when it is false. The ability of a statistical test to detect a specified difference if that difference exists. Directly proportional to the sample size.
1-beta. Beta is Type 2 Error aka Null hypothesis is false but you accept it.
Alpha (Type 1) and Beta (Type 2) are _______ proportional to each other and the sample size N
inversely
Methods to increase power
1) Increase Type 1 Error you are willing to tolerate
2) Increase the sample size
3) Increase the deviation from the null hypothesis you are willing to tolerate (big differences are easier to prove than small differences)
4) Decrease variability
5) Use a directional alternative hypothesis if appropriate.
6) Use the most efficient (most powerful) statistical test.
Dependent Variable
The variable we measure and compare
Independent Variable
The variable we manipulate
Descriptive Studies
Descriptive patterns of disease occurrence in relation to persons, place, and time. (Data provided essential to public health administrators and epidemiologists)
