researchmeth

 Experiment one manipulated variable - IVone labile measured variable-DV Correlational Study two measured variablesone called predictor (cause)one called predicted (effect) Quasi-Experiment one stable measured variable (SV) treated as the IVone labile measured variable treated as DV "Third Variable" a (typically unmeasured) variable that could be the cause of both the measured variables in a correlational studyTo fix, identifiy, measure, and co vary it out Spurious a significant relationship that is not causal (in either direction) Cross-lagged the correlation between one variable at one time and another variable at another time used to determine the more likely direction of causationif r2 X1Y2 > X2Y1 then X is probably the cause Partial (With respect to Z) the correlation between two variables after the effects of a third variable (Z) have been removed used to test (and rule out) a third variable explanation if prXY.Z=rXY then Z is not a cause of both X and Y External Validity the extent to which the results (from an experiment) will generalize to other situations Context Specificity when the results from an experiment or study are unique to the situation Person Specificity when the results from an experiment or study are unique to the subjects Convenience Sampling when only easily-recruited subjects are used Simple Random Sampling when all members of the population have a definable probability of being sampled, but no attempt is made to match the group sizes Proportional Stratified Random Sampling when the relative sizes of the groups in the sample are forced to be the same as those in the population Quota Sampling Most popular type of non-proportional stratified random samplingwhen the sizes of the groups in the sample are forced to be equal Survey or Questionnaire a structured set of items designed to measure attitudes, beliefs, values, or behavioral tendencies Scale a small set of items designed to measure a particular attitude, belief, value, or behavioral tendencyLikert: sets of strongly agree thru strongly disagree itemsGuttman: sets of ascending questionsThurstone: check all that apply (that are worth varying points)Semantic Differential: indicate position between opposite pairs Naturalistic Observation studying behavior in everyday environments without getting involvedkey threat: reactivity (secondary observer bias) Participant Observation studying behavior from within the target group key threat: standard experimenter bias (secondary observer bias) note: Participant observation is not often possible since no consent observation can only occur when and where there is no reasonable expectation of privacy Observer Bias when the beliefs or expectancies of the observers influence what is recordedinter-coder reliability must be at least .90 Experimenter Bias in general, when the beliefs and or expectancies of the experimenter end up altering the resultsstandard experimenter bias: occurs when the experimenter behaves differently when collecting data in different conditions (experimenter reactivity)defenses: remove experimenter or double-blindobserver bias is when only the recording of data is altered by the beliefs of the observerdefenses: checklists and or partial sampling Ex-post-facto Quasi Experiment when you take only one sample and then divide the subjects into the groups after-the-fact Planned Quasi-Experiment when you take separate samples for each of the groupsnote: this is another good example of the effort vs quality trade-off Longitudinal Study (aging) when you follow the same subjects over timemajor unique threat is time-frame (zeitgeist) effects Cross-Sectional Study (aging) when you take separate samples for each age group (at the same time)major unique threat is cohort effects Solution to both longitudinal and cross sectional: run a hybrid study and verify same results either way Decision Tree Domain: are you studying hidden, internal variables or behavior? This determines whether to use a survey or observationSampling: how much does this depend on who is measured? determines whether some fancy method (stratified, proportional, random) must be usedCausal Logic: is one of my variables either highly stable or the passage of time? determines whether one of the specific designs is used Directionality Problem it could be that X causes Y or that Y causes X to determine, run a cross-lagged study AuthorAnastasia ID48557 Card Setresearchmeth Descriptiontest 3 Updated2010-11-10T00:13:00Z Show Answers