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99 Cards in this Set
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repeated measures designs

RANDOMIZED GROUPS DESIGNS: diff. participants assigned each of conditions in and exper.
(aka: btwn group design diff behavior diff groups) W/IN SUBJ DESIGN: diff accross contitions w/in single group participants (aka: repeated measures design) 

type IV

ENVIRO. MANIPULATIONS: exper. conditions modified of participants physical or social envior.
CONFEDERATES: accomplices of researcher INSTRUCTIONAL MANIP: vary IV through verbal instructions participants recieve INVASIVE MANIP: create physical changes in participants body through surgery or drugs 

Experimental or Control groups

EXPERIMENTAL: recieve IV dosage
CONTROL: recieve 0 level IV (NOTE: not always necessary use control) 

Assess impact IV

many exper. fail
IV not manip. sucessfully IV not strong enough PIOLT TEST: try them out handful of people before actually start exper assure level IV enough be detected MANIP. CHECK: ? design determine whether IV was manip. sucesfully SUBJ. VARIABLES: personal char. of research participants (ex: age/gender/ self esteeme/extraversion 

DV

response measured in study
ex:how many words 

Assign of participants conditions

 test IV assume groups participants roughly equivalent beginning of study
want to be confident diff. produced by IV could be diff. at the start!!! 

simple random sample

place participants exper. conditons every participant has = chance being placed in condition
EX: flip coin 

Matched random assignment

up similarity among exper. groups
match var. pretest measure of DV put in clusters/ blocks of size K= #conditions in exper answer smae put into cluster w/ others answered the same each exper. conditon contains participants whos posess comparable level of memory ability 

door in the face effect

unreasonable offer followed by smaller offer = will accept it


experimental allows us to test direct hypoth. about _______ of behavior

causes


Experiment:
3 properties 
*research assigns participants to conditions and manipulates at least 1 IV
1. vary at least 1 IV assess effects participants behavior 2. power assign part. various exper. conditions a way assums initial equivalence 3. control extraneus var. may influence participants behavior 

Manip. IV

vary across effects diff. conditions behaviors


IV

 2 or more levels
*Conditions*  diff levels IV in experiment differ quanity each participant obtains 

advantages w/in subj designs

more powerful(ability to detect effects IV)
participants each condition identical eliminate indiv. diff. require few participants 

disadvantages w/in subj designs

ORDER EFFECTSeach participate recieves all levels IV and order which recieved affect behavior
Use COUNTERBALANCINGpresent in diff order to diff participants all possible orders used may choose smaller subset possible orderings LATIN SQUARE each condition appears once each ordinal position and each precedes and follows every other condition CARRYOVER EFFECTS effects one level of IV still present when another level IV intoduced 

experimental control

eliminationg or holding constant extraneous factors might affect outcome of the study


systematic variance

(btwn group variance)
part of total variance reflects diff. among experimental groups if IV had effect observe systematic dif. scores various exper. conditions scores differ systematically btwn conditions systematic variance exixts in scores 

treatment variance

proportion variance part. scores due to IV (aka:primary variance)


confound variance (2ndary variance)

portion of variance partic. scores due to extraneous variables differ systematically btwn exper. groups
must be eleminated @ all costs!! 

error variance (w/in groups variance)

result unsystematic diff. among participants
treat each participant differently introduce randome variability into the data does NOT invalidate experiment 

an analogy

Total = treatment+ confound + error
variance var. var. var. __________________ ______ systematic + unsystem. variance variance 

ideal exper

up treatment variance/ eliminate confound variance/ down error var.


internal validity

degree to which researcher draws accurate conclusions effect IV
eliminate potential sources confound var. CONFOUNDING OCCURS: if something other than IV differs in systematic way fatal flaw in exper. achieved through exper. control 

threats to Internal Validity

introduce alternative rival explainations
no one likely take them seriously 

Threats to Internal Validity:
6 threats 
1.BIASED ASSIGN OF PARTIC. TO CONDITIONS:introduce possibility effects due to nonequivalent groups rather than IV
2.DIFFERENTIAL ATTRITION:loss of participants during study when rate of sttrition differs across exper conditions internal validity is weakened 3.PRETEST SENSITIZATION:may sensitize participants to IV so react diff. to IV than would react had not been pretested 

Threats to Internal Validity:
6 threats 
4.HISTORY:effected by extraneous events occur outside research setting
*event measuring happened to them already that week 5.MATURATION:occurs long span of time create confounds dev. maturation = go through age related changes 6.MISC. DESIGN CONFOUNDS:every participant treated same way can be controlled for 

experiment expectancies:
deman char. and placebo effects 
affect by beliefs what SHOULD happen in experiment


experimenter expectancie effects:
Rosenthal Effect 
researcher expectations about study influence participants reactions


demand char.

assumptions about nature of a study can also affect outcome (try to figure it out)
how participants should behave and how researcher expected you to repond eliminate this conceal purpose of exper. from participants use double blind procedure 

placebo effects

psychological or physiological chage occurs as a result of mere suggestion chage will occur
PLACEBO CONTROL GROUP administered ineffective treatment 

error variance

less fatal problem than confound variance
seldom eliminated from experiemtnal designs 

sources error variance:
"static" in an exper. 
1.INDIV DIFF:prexisting diff
use homogeneous sample=>same people ex: use littermates 2.TRANSIENT STATES:healthy vs. ill current moods, attitudes, and physical conditions affect behavior 3.ENVIRO EFFECTS:where study conducted external noise distraction collect data diff. parts day 4.DIFFERENTIAL TREATMENT:treat exactly same all exper. conditions plesant/unpleasant/attractive/M vs. F 5.MEASUREMENT ERROR:cause scores vary unsystematic ways 

exper. control and generalizability:
E's dilemma 
up exper. controls = artifical situations and highly specific
more controlled = more difficult is to generalize findings EXTERNAL VALIDITY:degree which results obtained one study be replicated or generalized to other samples, research settings, procedures generalizability research results to other settings E'S DILEMMA:conflict btwn internal and external validity choose btwn interna and external validity usually chose INTERNAL over external 

Brennan et al. (1990)

50 Q about celebs > 15 undergrads
x = 10.5 elicited tip of tounge (range = 422) T of T =>1.repeat question 2.picture indiv 3. initials 

Piliguin et al (1995)
"bystander" 
on NY subway =>elderly gentleman (white) had cane
=>fell/ clapses 1. would ugly birthmark face impact willingness offer assistance => 2.medical intern same subway car 

The Sleeper Effect

passage time up persuasiveness of an idea
ex:low fat diet pizza Rate: 110: they rate 5 get SE commercial has to be placed in a source mistrust than if released by scientist that company =>SE artifact memory =>encode article and ads =>dont give crediability over time =>article and ad fades away 

oneway designs

exper. designs which only 1 IV is manipulated


2 group exper. design

only 2 levels of IV (2 conditions)
min 2 conditions needed so can compare to other 

Assign Participants to Conditions

One way designs: randomized groups design/ matchsubj/ repeated measures/ w/in subj. designs
RANDOMIZED GROUPS DESIGN:btwn subj. participants randomly assigned to one of two or more conditions MATCHED SUBJ. DESIGNS: participants matched into blocks on basis of a var. researcher believes relevant to experiment then assign to exper or control REPEAT MEASURES (W/IN SUBJ) DESIGNS: each partic. serves in all exper. conditions 

Posttest and Pretest Posttest Designs

only way exper. designs above called posttest designs
POSTTEST DESIGNS:DV is measured ONLY after the exper. manip has occured 

Pretestposttest designs

measure DV twice: onece before IV manip and after
ADVANTAGES: 1.Partic. did not diff w/ respet to DV at beginning of exper (efectiveness documented) 2.see exactly how much IV changed partic. behavior (baseline data) 3.more powerful 

drawback posttest and pretest designs

may sensitize participant to respond to IV differently than would if not pretested
posttest diff. btwn conditions indicate IV has an effect each 3 designs can be used as posttest and pretestposttest design 

factorial nomenclature

use factorial designs to study indiv. and combined effects of 2 or more factors w/ in single exper.
2 way factorial designs = 2 IV 3 way (F) designs = 3 IV and so on 

factorial designs

written as 2x2/ 3x3 tell how many IV there are and how many levels there are
*2x4 =2 IV = 1 w/ 2 and 1 w/ 4 levels 2x2x2 = 3IV each var. has 2 levels a)2x2 b)3x3 c)4x2 a)2x2x2 b)2x2x4 tell # conditions factorial design has mult. #'s in design (2x2 = 4) 

randomized groups factorial designs

participants assign randomly to one of possible combinations of IV


matched factorial design

involves 1st matching partipants to blocks on basis some var. that corr w/ DV as many partic. in each matched block as there are exper. conditons


repeated measures factorial design

requires all participants to participate in every exper. condition
larger designs order and carry over effects problem! 

mixed factorial design

combines one or more btwnsubj. var. w/ one or more w/ in subj variable
ex:visual clif exper. 

main effects and interactions

factorial designs used examine var scores due to
1.Indiv effects each IV 2.combined or interactive effects IV 3.to error var. 

main effect

effect single IV in a factorial fesign
ignore effects other IV 

interactions

the effect of one IV differs across levels of other IV (diff effect 1 level of another IV) than has at another level of that IV say IV interact and an interaction btwn IV is present


factorial design w/ 2 IV

1.main effect A (ignore B)
2.main effect B (ignore A) 3.interaction A and B 

factorial design w/ 3 IV

1.examine effects each 3 IV seperately (a,b,c)look indiv efects interactions
2.look at 2 way interactions A by B (ignore C), A by C (ignore B) tells if IV diff at diff levels of another IV 3.info combined effects all 3 IV 3 way interaction A by B by C only 3/4 IV max used exper. 

subj variable

age, sex, intelligence, ability, personality and attitudes moderate or qualify the effects of situational forces on behavior
react diff in diff. situations (everyone) 

expericorr (experimentalcorrelational)

combine features of an experimental design which IV are manip and features of corr designs in which subj. var. are measured


uses of mixed designs

1.investigate generality of an IV effect
ex:only partipants w/o certian char 2.researchers use expercorr in attempt understnad how certian personal char. relate to behavior under varying conditions 3.split into groups participant var. researchers make participants in exper. condition homogeneous down error variance 

classify participants into groups

mixed designs classify into groups on basis of measured participant variable (gender etc.) then randomly assign that group to levels to IV


median split procedure

researcher identifies median participants scores var. of interest then classifies participants w/ scores below median low on var and sores about median as up on variable
If these used: lead to bias results can be problematic 

cautions in interp results of mixed designs

can not include "causes"
subj. var. measured rather than manip. 

moderator variable

a var. that qualifies or moderates the effects of another var. on behavior


quasiexperimental designs

(not true exper)
lacks random assignment participants to conditions/compares people in groups already exist or w/in single group participants before and after some event has occured 

quasi independent variable

used to indicate the var is not a true IV manip. by the researcher rather is an event occured for other reasons
threats internal validity present quality quasi exper. depends on how many threats there are to internal validity it sucessfully eliminates 

one group pretestposttest design

a preexpermental design which a group of participants is tested before and after quasi indep. var. has occured fails to control for all threats internal validity
DO NOT USE! effects not looked at:maturation effects, history effects, testing effects 

effect of one group pretest
postest design: regression to the mean 
tendency for extreme scores in distribution move, or regress toward the mean of the distribution w/ repeat testing


preexperimental design

lacks necessary controls to minimize threats to internal validity/ not involve adequate control or comparison groups


nonequivalent control
group design 
looks for one or more groups participants appear to be reasonably similar to the group that recieved quasi IV
2 var = posttest and 1 pretest and posttest 

nonequivalent groups posttest
only design 
measure both groups after one of them recieved quasiexper. treatment
before = baseline not eliminate all threats to internal validity 

local history affects and
selection  by history interaction 
1. something happen to one group doenst happen to another
2. "history" effect occurs in one group but not in the other 

time series designs

measure DV on several occasions before and one several occasions afer quasi IV occurs


simple interrupted
time series design 
taking several pretest measures before introducing IV (or quasi IV) then take several posttest measures aferwards
(01,02,03,04 * 05,06,07,08) interuption quasi IV 

contemporary history

not rule out that observed effects where due to another event occured at same time as quasi IV


interrupted time seires w/ a reversal

observe participants behaivor when quasiIV or treatment introduced then removed
(01,02,03,04 x 05,06,07,08 x 09,010,011,012) 

interuruped time series design w/ mult. replications

reintroduce IV observe effects and remove second time
(01,02,03 x 04,05,06 x 07,08,09 x 010,011,012 x 013,014,015) 

interruped time series design w/ mult replications: LIMITATIONS

1. research has not power remove IV (seat belt laws)
2. effects some quasi IV remain even after var. itself is removed 3. removal quasi IV may produce chages not due to effects of var. per se 

Control Group Interrupted
Time Series Design 
perform analysis on group recieved the quasi IV and on nonequivalent control group did not recieve the quasi IV
helps rule out certian history effects 

longitudinal desings

the quasi IV is time itself
01,02,03,04,05 GOAL: uncover dev. changes occures function of age but something other dev. has produced observed changes 

longitudinal designs:
drawbacks 
1.difficult obtain samples participants affree be studies against again over long period of time
2. trouble keeping track of participants many move and may die 3. requires great deal time, effort, and money 

longitudinal designs

examine how indiv. participants change w/ age
important effects of time and aging on dev. 

crosssectional designs

compare groups diff. ages at single pt in time
age related changes DRAWBACK:gernerational effect people diff ages differ in agge perse but also conditions under which their generation grew up track same age diff. yrs. in future 

eval. quasi exper. designs

see if vary covary > corr. and ANOVA


up confidence in quasiexper.
results 
"patch" up basic designs to provide most meaningful and convincing data possible
more IV better 

Problem:
Multi tests inflate Type 1 error 
type 1 error up when perform greater # of tests
more likely draw invalid conclusions about effects IV problem make type 1 error use (1  (1alpha)c c = # of tests 

Bonferroni adjustment

divide desidred alpha level by # of tests plan to conduct
DRAWBACK: problem type 1 error down problem type 2 error up 

Analysis of variance
(ANOVA 
stat procedure used to analyze data from designs w/ more than 2 conditions
determines any sets of means diff from another using single stat test holds alpha levle @ .05 

rationale behind ANOVA

FTEST: ratio variance among conditions (btwn groups) to variance w/in conditions (w/in groups)
larger the better test to see if estm diff. btwn condition means due to error variance 

one way design w/ single IV

ANOVA breaks total var into 2 components
1. systematic variance 2. error variance 

total sum of squares

SUM OF SQUARE: reflets total amount of variance in set of data
TOTAL SUM OF SQUARE: caluculate 1. subtract mean each score 2. square diff 3. add them up = total amount of variability in set of data 

sum of squares w/in groups

sum of variances of the scores w/ in particular experimental conditions
express variability in data NOT due to IV or = error variance 

means square w/in groups

divide w/ in groups variance by w/ in groups df obtain quantity
provides estm. ave. w/in groups or error variance 

sum of sq. btwn. groups

var set scores assoc. w/ IV; sum sq. diff btwn each condition mean and grand mean
estm. systematic var 1. subtrack grand mean each group means (small means dont differ much or IV NO EFFECT) 2. sq. diff 3. mult. each sq diff by size group 4. sum across groups 5. divide K 1 (k = # of groups) 6. divide by (k1) = mean sq. btwn groups  our estm systemaic or btwn groups variance 

Ftest

calculate ratio btwn groups variability to w/in groups variablitiy each effect testing
IV no effect = numerator and denominator are estm. same IV effect numerator larger than denominator value F exceeds critical value F on table at least 1 condition means differ orthers = IV has effect 

follow up tests

1. calculate means signif. effects (a leave b out and vice versa)


main effects (ME)

2 means differ systematically, inspect means find out direction and magnitude
signif. ME indicates diff. exixts btwn 2 of 3 conditions means does not indicate which means differ from which 

follow up tests
(aka: post hoc test or mult comparisons) 
identify which means differ signif
aka:LSD test, Tukey's test, Scheffe's test done only if F test is significant 

interactions

 SIMPLE MAIN EFFECT: effect 1 IV at a particular level of another IV
show which conditoin means w/ in interatction differ from each other 

btwn subj. and w/in subj
ANOVA's: Multi analysis of variance 
MANOVA: test diff btwn means of 2 or more conditions 2 ore more DV simultaneously


conceptually related DV

several DV all tap some construct
combines info 10 DV new composit var. then analyse whether participants scores new composit var diff among exper. groups 

Inflations of Type 1 error

MANOVA contols this


How MANOVA WORKS

1. reate new composit var. weighted sum of orginal DV
CANONICAL VAR: composite var. is calculated by summing 2 or more DV have been weighted accoring to ability to differentiate among groups of participants produce single index var. of interest 2. multivariage version Ftest is performed to determine if partic. scores canonical var. differ among exper. condtitions 3. now can perform ANOVA w/ out talk of Type 1 Error if significant 