Study Design: FDA Approval
Terms
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Clinical Trials
Preclinical Phase  animal or cellculture studies

Clinical Trials
Phase I  treatment safety is tested in a few human volunteers

Clinical Trials
Phase II  small randomized blinded trial that tests for side effects by a range of doses and surrogate measurements of the outcome variable

Clinical Trials
Phase III  larger randomized clinical trial used for hypothesis testing and determinations of treatment safety

Clinical Trials
Phase IV  following FDA approval, large study (random or nonrandom) used to determine serious side effect rate and other drug uses
 PreExperimental Design

weakest of the research designs. Subject to many threats to internal and external validity.
Characterized by lack of a control group, sensitivity to threats and poor generalizability. Ex: oneshot case study, one group with pre/post tests, static group comparison  QuasiExperimental Design
 more rigorous than preexperimental, but less robust that true experimental design. Generally lacking randomization or multiple measurements make testing effects a problem. Ex: nonequivalent control group, time series design
 Efficacy
 whether the intervention can be successful when it is properly implemented under controlled conditions
 Effectiveness
 whether the intervention typically is successful in actual clinical practice
 Drug testing in the US is currently biased toward the minimization of "Type I" error (5%), that is, toward minimizing the chance of approving drugs that are unsafe or ineffective
 This regulatory focus of the FDA ignores the potential for committing the alternative "Type II" error (20%), that is, the error of not approving drugs that are, in fact, safe and effective
 Intention to Treat Analysis
 Specifies how to handle noncompliant patients in a randomized control trial. Requires that patients be analyzed in the groups they were randomized into, regardless of whether they complied with the treatment they were given
 What if only included compliant patients?

Drawbacks:
1. Groups defined by compliance are no longer randomized and are thus subject to biases.
2. Groups defined by compliance may not represent the practical impact of the treatment.  Reliability
 the external and internal consistency of a measurement. In the abstract, whether a particular technique, applied repeatedly to the same object, would yield the same result each time.(accuracy)
 What are three forms of Reliability?

1. Instrument reliability
2. Intrarater reliability
3. Interrater reliability  Instrument reliability
 consistency of a measurement by a particular instrument
 Intrarater reliability
 consistency with which individual takes measurements (protocols are helpful)
 Interrater reliability

consistency of measurements between or among >1 individual
** 2 P rule (protocol and practice)  Validity
 the degree to which a scale is in fact consistently measuring the variable that it is designed to measure (precision); appropriateness of a given measure
 2 Forms of Validity

1. Measurement (test)
2. Design (experimental)  4 Types of Measurement Validity

1. Face
2. Construct
3. Content
4. Criterion 
Measurement Validity
Face Validity 
Does the particular measurement or method appear to be appropriate?
often just expert opinion
weakest form 
Measurement Validity
Construct Validity 
Is the measurement based on theory?
the degree to which a measure relates to other variables as expected within a system of theoretical relationships (based on logical relationships) 
Measurement Validity
Content Validity  Is the test broad enough to address the scope of content?

Measurement Validity
Criterion Validity  How well does the test perform and is it useful when judged against a standard?

Measurement Validity
Criterion Validity
Predictive Validity  Can the test predict a specific outcome?

Measurement Validity
Criterion Validity
Concurrent Validity  Does the test perform as well as an accepted test?

Design Validity
Internal Validity  factors and events other than the IV which may cause changes in the DV

Design Validity
External Validity  generalizability of the conclusions drawn from the study; degree to which the results of a study generalize to the population
 Threats to Internal Validity

1. Temporal or timebased effects: history, maturation, attrition.
2. Measurement effects: testing, instrumentation sampling, statistical regression to the mean  Threats to External Validity

1. Threats related to population used: subjects accessibility to the study and subjecttreatment interaction.
2. Treats related to the environment in which the study takes place: description of the variables, multiple txs, Hawthorne effect, Rosenthal effect  Design Shorthand

R = randomly assigned or selected
X = tx
Xo = no tx or control cond.
O = measurement  When does correlation impy causation?
 When the data from which the correlation was computed were obtained by experimental means with appropriate care to avoid confounding and other threats to the internal validity of the experiment
 Correlation
 relationships between two or more variables to explain the nature of relationships in the world and not to examine cause and effect
 Causation

one variable causes another variable
1. Cause must precede effect
2. two variables are correlated with one another
3. correlation between the two variables cannot be explained away as being the result of the influence of a third variable that causes both of them  What is experimental uncertainty caused by?
 Random errors or systematic errors
 Random errors
 statistical fluctuation (either direction)in the measured data due to the precision limitations of the measurement device; caused by experimenter's inability to take the same measurement in exactly the same way to get exactly the same number
 Systematic Errors
 reproducible inaccuracies that are consistently in the same direction; due to a problem which persists throughout the entire experiment

Survey Research
Census  survey of the population

Survey Research
Poll  for political information or opinion

Survey Research
Survey  from a sample of the population
 Strategies to Increase Response Rate of a Survey

1. Advance notification
2. Cover letters
3. Multiple mailings, reminders
4. Stamped, return envelopes
5. Separate postcard to request results
6. Incentives
7. Anonymity and confidentiality  3 Factors Needed to Determine Sample Size

1. The "effect size" (a measure of variability between variables)
2. Level of significance (0.05 is generally used)
3. Statistical power  to prevent type I errors  Type I error
 rejecting a null hypothesis when it should have been retained (alpha 5%)
 Type II error
 retaining a null hypothesis when it should have been rejected (beta 20%)
 Statistical Power
 the probability of rejecting a null hypothesis that is, in fact, false (needs to be at least 80%)
 Confidence Interval
 a range of values for a variable of interest constructed so that this range has a specified probability of including the true value of the variable. End pts of the confidence interval are called confidence limits (usually created at the 95% level)
 Absolute Risk
 An individual's risk of developing a disease over a time period
 Relative Risk
 Used to compare the risk in two different groups of people
 Number Needed to Treat
 How many people need a treatment in order to prevent one additional death in an amount of time
 Odds Ratio
 Dividing the odds in the treated or exposed group by the odds in the control group