Producing Data (C11-13 BVD) C13: Experiments and Observational Studies

* An Observational Study observes individuals and measures variables of interest but does not attempt to influence the responses. * Prospective – identify participants now and “follow” into future * Retrospective – identify participants now and “mine” existing past data about them

* An experiment deliberately imposes treatment to subjects and measures responses. * Principles of Good Experimental Design: * 1. Control for lurking variables in a comparative design. * 2. Randomly assignment of subjects to treatment. * 3. Replicate – use enough experimental units in each treatment group so that differences between groups can be distinguished from chance variation.

* Lurking variable = a variable not among the explanatory or response variables in a study that may influence the response variable. * Confounding = occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other. * (Beware of using this terminology incorrectly on AP exam – if in doubt – choose a different word.)

* Treatment = A treatment is a combination of specific values of all the explanatory variables of an experiment. Every possible combination of x- variables must be assigned to a group. * Experimental units/subjects = the people/objects/animals to which treatments are applied. * Factor = another word for an explanatory variable * Level = a specific value of a factor (like 1 mL water vs. 2 mL water vs. 0 mL water)

* Control Group – The treatment group that receives “baseline” levels of all factors for comparison purposes. * Placebo = a treatment that has no active ingredient. * Blinding = preventing subjects (and possibly those who interact with subjects) from knowing which treatment group they’re in. * Statistically Significant = An observed effect so large that it would rarely occur by chance.

* Completely Randomized Design * 1. start with x subjects/units * 3. divide subjects randomly into groups – 1 group for each treatment * 4. apply treatments * 5. measure response variable and compare groups.

* Randomized Block Design * 1. start with x subjects/units * 2. separate into pre-existing blocks – units within a block should be alike * 3. divide each block into groups – 1 group for each treatment * 4. apply treatments * 5. measure response variable and compare within block. Do not compare one block with another.

* Matched Pairs Design – used for comparing two treatments * 1. start with x subjects/units * 2. separate into pairs of experimental units. OR separate into individuals who will receive both treatments * 3. randomly assign which individual in pair gets which treatment OR randomly assign which order treatments are applied to each individual * 4. apply treatments * 5. measure response variable and compare within pairs OR individuals.

* Random selection AND random assignment – may generalize results to larger population and infer cause/effect * Random selection only – may generalize to larger population but may NOT infer cause/effect * Random assignment only – may infer cause/effect but may NOT generalize to larger population * Neither random selection nor assignment – may NOT generalize to larger population or infer cause/effect

* Placebo effect * Voluntary consent – children, mentally disabled/ill? * Harm – review boards, animals, etc. * Publishing concerns * Unnatural settings