Chp. 11 Verms - More on Experiments: Confounding and Obscuring Variables

design confound 1

alternative explanation because explanation was poorly designed

selection effects 2

different independent variable groups have systematically different types of participants

order effects 3

the outcome might be caused ty the independent variable, but also be caused in order in which the levels are presented

one-group, pretest/posttest design

experiment in which a researcher recruits one group of participants; measures them on a pretest; exposes them to a treatment, intervention, or change; and then measures them on a posttest - “the really bad experiment”

maturation effect 4

a threat to internal validity that occurs when an observed change in an experimental group could’ve emerged more/less spontaneously over time; solution: include comparison group

history threat 5

a threat to internal validity that occurs when it is unclear whether a change in the treatment group is caused by the treatment itself or by an external or historical factor that affects most members of the group; solution: include comparison group

regression threat 6

a threat to internal validity related to regression to the mean, a phenomenon in which any extreme finding is likely to be closer to its own typical, or mean, level the next time it is measured (with or without the experimental treatment or intervention); solution: include comparison group & careful inspection of the pattern of results

regression to the mean

phenomenon in which an extreme finding is likely to be closer to its own typical, or mean, level the next time it is measured, because the same combination of chance factors that made the finding extreme are not present the second time

attrition threats 7

in a pretest/posttest, repeated-measures/quasi-experimental study, a threat to internal validity that occurs when a systematic type of participant drops out of the study before it ends; solution: remove that participants from the pretest average too if the participant drops out, check the pretest scores of the dropouts

testing threat 8

in a repeated-measures experiment/quasi-experiemnt, a kind of order effect in which scores change over time just because participants have taken the test more than once (includes practice effects); solution: might abandon a pretest altogether & use a posttest-only design, comparison group might help

instrumentation threat 9

a threat to internal validity that occurs when a measuring instrument changes over time; solution: pretest & posttest measures are equivalent, might retrain raters

selection-history threat

a threat to internal validity in which a historical or seasonal event systematically affects only the participants in the treatment group or only those in the comparison group, not both

selection-attrition threat

a threat to internal validity in which participants are likely to drop out of either the treatment or comparison group, not both

observer bias 10

a bias that occurs when observer expectations influence the interpretation of participant behaviors or the outcome of the study - can threaten both internal & construct validity

demand characteristics 11

a cue that leads participants to guess a study’s hypotheses or goals; a threat to internal validity (also experimental demand)

double-blind study

a study that uses a treatment & a placebo group and in which neither the researchers nor the participants know who is in which group

masked design

a study design in which the observers are unaware of the experimental conditions to which participants have been assigned

placebo effect 12

a response or effect that occurs when people receiving an experimental treatment experience a change only because they believe they are receiving a valid treatment; solution: include comparison group, (participants don’t know if in placebo/control group)

double-blind placebo control study

a study that uses a treatment group and a placebo group and in which neither the researchers nor the participants know who is in which group

null effect

a finding that an independent variable did not make a difference in the dependent variable; there is no significant covariance between the two (also null result)

ceiling effect (too little between-groups difference)

an experimental design problem in which independent variable groups score almost the same on the dependent variable, such that all scores fall at the high end of their possible distribution

floor effect (too little between-groups difference)

an experimental design problem in which independent variable groups score almost the same on a dependent variable, such that all scores fall at the low end of their possible distribution

manipulation check (too little between-groups difference)

in an experiment, an extra dependent variable researchers can include to determine how well a manipulation worked

noise (too much within-groups)

unsystematic variability among the members of a group in an experiment, which might be caused by situation noise (individual differences/measurement error)

measurement error (too much within-groups)

degree to which the recorded measure for a participant on some variable differs from the true value of the variable for that participant can be random/systematic, that scores are biased too high/low; solution: use reliable, precise tools, measure more instances

situation noise

unrelated events or distractions in the external environment that create unsystematic variability within groups in an experiment

power

the likelihood that a study will show a statistically significant result when an independent variable truly has an effect in the population; large sample benefits: large sample make confidence intervals narrow, better chance of estimating real effects