Psych Ch. 13

differs from a true experiment in that the researchers do not have full experiments control --still studying the effect of an IV on a DV -often because people can not be assigned to specific levels of intended IV-gender, age (participant variables) --why do people do them? ---convenience, ethics, external validity (at expense of internal) -opportunity to observe-real world effect

different participants at each level of the independent variable -nonequivalent control group design -nonequivalent control group pretest/posttest

a quasi experiment study that has at least one treatment group and one comparison group--but participants have no been randomly assigned to the two groups --independent groups (between subjects) -Head start study -match students based on school exams- one who qualifies financially for head start and one that doesn't- test both at later date

participants not randomly assigned and were tested before and after the intervention -plastic surgery example-tested on life satisfaction before and after surgery (tested twice) --group only exposed to 1 level-people either get the surgery or don't -only measured twice -you compare one group (non-surgery group) to the other (surgery group)

-within subjects --same group of people exposed to different manipulations of the IV -different from an experiment because researcher takes advantage of an already scheduled event/policy/chance occurrence to manipulate IV --ex:interrupted time-series design, nonequivalent control-group interrupted time-series design

repeated measures quasi experiment (within subjects) -a quasi experimental study that measured participants repeatedly on a DV before, during, and after an "interruption" caused by event -measure the DV after each event (IV) (at least 3 times) --ex:decision fatigue/judge granting parole: DV=proportion of criminals granted parole IV/event=snack/lunch -television access and crime rate, crime rate measured before, during, and after introduction of television -one continuous line on a graph-should show change over time (after introduction of IV) -you compare measurement 1 of DV to measurement 2 of the DV-for the same group

combines nonequivalent control group design (independent) with interrupted time series design (within-subjects) -just like interrupted time series:measure DV before, during, and after introduction of IV (within subject) -measured crime rates before/during/after introduction of TV -but also have a control group (nonequivalent control group) -also compared larceny rates in cities that had television with cities that did not -two lines on a graph-experimental group should show change over time, and also show a greater change than the control group (to prevent against maturation threats)

-selection effects, maturation, attrition, history, regression, testing/instrumentation threats -design confounds -observer bias, demand characteristics, and placebo effects ---good experimental designs, and pattern of results can help rule out internal validity threats

threat to internal validity -only relevant for independent groups design -occurs when the groups at the various levels of the IV contain different types of participants -->it's not clear whether the IV or the different types of people caused the change in the DV -ex: head start -experimental group had impoverished children --solved with pretest/posttest, matched groups, or wait-list design

-solution to selection effects (threat to internal validity) with between groups (independent-groups) design -all participants plan to receive treatment, but are assigned to do so at different times --helps het same kind of people in both groups -cosmetic surgery example --can still be unethical depending on what the treatment is -random assignment? hopefully

-internal validity threat --some outside variable accidentally and systematically varies with the levels of the targeted IV -can lead to an alternate explanation --inspect data carefully to rule out design confounds

-internal validity threat --quasi experiment with pretest posttest design, when a treatment group shows an improvement over time, but it's unclear if the improvement was caused by the treatment of whether the group would have improved spontaneously without the treatment --design (include a comparison group) + pattern of results (different between the two groups) help eliminate maturation threats

-internal validity threat -when an external/historical event happens for everyone in the study at the same time as the treatment variable --can be especially relevant in quasi-experiments that rely on external factor to manipulate the key IV (ccc television broadcasting policies) -recession possible history threat for TV introduction and crime rates --comparison group--recession happened for all cities, but only cities with television had significant rises in larceny rates --selection-history threat=only happens in one group

-internal validity threat --when an extreme finding is caused by a combination of random factors that are unlikely to happen in the same combination again -head start-to create matched groups-paired high scoring head start kids with low scoring non-head start children--scores may have been caused by random factors--low scoring non-head start kids didn't get a good night sleep --wouldn't happen again at the posttest-->regression to mean -relevant for pretest/posttest-primatily when a group is selected for having extremely high or low scores (don't choose high/low scores=solution) --not usually a problem in true experiments because of random assignment

-internal validity threat --pretest/posttest when people drop out over time -only a problem when people drop out systematically --ex:least satisfied people stop reporting to questionnaires in cosmetic surgery exp. -just drop pretest scores of people you don't get posttest scores from

internal validity threat -a problem when the DV is measured more than once (pretest/posttest or within [repeated measures]) --participant changes as a result of being tested before -practice effect/fatigue effect --comparison group helps

internal validity threat -a problem when the DV is measured more than once --when a measuring instrument changes over time -comparison group helps --instrumentation threat was the actual result in the parole hearing and lunch break exp.

-internal validity threat --also threatens construct validity (observer's interpretations don't reflect real levels of DV) --expectations of the observer influence how they interpret the results -especially relevant for behavioral studies -double blind can help -carefully train coders+manual+multiple codes

internal validity threat -participants guess what the study is about and change their behavior in the expected direction --double blind study

internal validity threat -when participants experience actual change, but not as a result of the IV-as a result of their belief that they are receiving a legitimate treatment -double blind+comparison groups

real world setting increase external validity -still need to ask if experiments would generalize to other people/situations --dont have to ask if it would generalize to real world situations

-isn't ethical to withhold things like head start with random assignment-cant to a true experiment -even wait list designs still questionable

usually have successful manipulation of the IV (how well was the IV manipulated) --how well was the DV measured is more important -can be questionable in behavioral DV-with observer bias

-need to address how large the group differences were (effect size) -were the results statistically significant

-independent groups design are similar to correlational studies --quasi=people not randomly assigned --correlational=two measured variables -have similar internal validity questions --quasi=selection effects/design confounds --correlational=lurking variables -quasi-experiments attempt to have internal validity-matched groups, wait-list designs, or a natural comparison group

-experiments that study only a few individuals --external validity=how a sample is selected (more important that number of people in sample) -instead of gathering a little information from a large sample, they obtain a lot of information from just a few cases -researchers often study special cases, taking advantage of special medical cases (similar to quasi experiment)-ie split brain --almost always repeated measures

sample is restricted to one animal/person

-Large N: participants are grouped and data is represented as a group average -small N: each participant is treated as a separate experiment (almost always repeated measures) and individuals data is presented

corpus callosum cut in severe seizure patients --people with condition were studied to see how the different hemispheres of the brain act independently -speech=left hemisphere/right eye -left hemisphere responsible for speech, storytelling/cause and effect, and sense of self --how much can you conclude from such a small N sample ---experimental control, strong manipulation, and replication help you conclude more

experimental control, strong manipulation, and replication help you conclude more

-how much can you conclude from such a small N sample control possible third variables? -controlled the movement of participants eyes to control which hemisphere saw what

--how much can you conclude from such a small N sample -making sure you manipulate the IV enough to cause a significant change in the DV (making your levels different enough from one another) -tasks that would be easy for normal brain people and impossible for split brain people were used (showed the change in DV)

-how much can you conclude from such a small N sample --are the results among your small number of participants similar? -results were replicated among 5 split-brain patients

-a few people may not represent the whole population well (data was consistent among 5split-brain patients, but they were all severely epileptic=systematically different brains that the general population) - it is often unethical to create the necessary comparison group

similarities in animal studies, brain imaging, and weight of evidence can support a claim and lead to a parsimonious theory (about brain organization) -external validity

small N designs that attempt to modify behavior -alzheimer's new memory strategy, special ed teacher discourages face touching, --can have many internal validity questions

Behavior Change studies (small n) -a researcher observes behavior for an extended baseline period before beginning a treatment --if baseline is stable-behavioral change during the treatment period was more likely a result of the IV -better than single pretest (in pretest-posttest) extended pretest period lowers the chance that a single spontaneous event occurred at the same time as the pretest and changed the behavior (rule our maturation/history/and regression threats)

Behavior Change studies (small n) -researchers stagger their introduction of an intervention across a variety of contexts, times, and situations --special ed girl touched her face/objects/hair- introduced overcorrections for each behavior separately -each decreased after overcorrection was applied (overcorrection works) -if a single event was responsible for the change, all of the behaviors would have changed at once instead of staggering with overcorrection -baseline can also be different situations-correct a behavior at work/home/school ---can be different people, behavior modification for 3 children in the same class, one at a time -provide automatic comparison condition

Behavior Change studies (small n) -researcher observes subject with and without treatment but takes the treatment away for a while (reversal period) to see whether the problem returns (reverses) --test internal validity-if treatment is causing change, problem should return when it is removed -only really works when treatment doesn't cause lasting change --ex:doesn't work for education-cant relearn the alphabet -questionable ethics of removing a treatment that works (depression)

-internal validity because of repeated measures/within group, replication, experimental control, strong manipulations, pretest/posttest, baseline designs and reversals -external validity-triangulation + weight of evidence + specific population to generalize results to, and can still be useful without generalizing -construct-multiple observers + interrater reliability for behavior -statistical-graphs, effect size (by what margin did client's behavior improve) not traditional statistics