PSYC512: Research Methods PSYC512: Research Methods Lecture 15 Brian P. Dyre University of Idaho.

PSYC512: Research MethodsPSYC512: Research Methods

PSYC512: Research MethodsPSYC512: Research MethodsLecture 15Lecture 15

Brian P. DyreBrian P. Dyre

University of IdahoUniversity of Idaho


Lecture 15 OutlineLecture 15 Outline Review of Lecture 14Review of Lecture 14

Multi-factor research designsMulti-factor research designs Today: other specialized research designsToday: other specialized research designs

Statistical “nuts and bolts” in conducting Statistical “nuts and bolts” in conducting hypothesis tests of meanshypothesis tests of means

Combining experimental and correlational Combining experimental and correlational designs (Analysis of covariance or ANCOVA)designs (Analysis of covariance or ANCOVA)

Quasi-Experimental DesignsQuasi-Experimental Designs Developmental DesignsDevelopmental Designs Small-n designs and Psychophysical Small-n designs and Psychophysical

MethodsMethods


Statistical “nuts and bolts” in Statistical “nuts and bolts” in testing hypotheses about testing hypotheses about meansmeans The central limit theoremThe central limit theorem

The mean of the sampling distribution of means is The mean of the sampling distribution of means is equal to the mean of the population from which the equal to the mean of the population from which the samples were drawn. samples were drawn.

The variance of the sampling distribution of means is The variance of the sampling distribution of means is equal to the variance of the population from which the equal to the variance of the population from which the samples were drawn divided by the size of the samples were drawn divided by the size of the samples. Expressed as the standard deviation: samples. Expressed as the standard deviation:

If the original population is distributed normally (i.e. it If the original population is distributed normally (i.e. it is bell shaped), the sampling distribution of means will is bell shaped), the sampling distribution of means will also be normal. If the original population is not also be normal. If the original population is not normally distributed, the sampling distribution of normally distributed, the sampling distribution of means will increasingly approximate a normal means will increasingly approximate a normal distribution as sample size increases. (i.e. when distribution as sample size increases. (i.e. when increasingly large samples are drawn) increasingly large samples are drawn)

NX /


Does a sample mean Does a sample mean significantly differ from a significantly differ from a population mean?population mean? of population is knownof population is known

z test of sample meanz test of sample mean

of population is of population is estimated as estimated as ss t-test of sample meant-test of sample mean As N approaches As N approaches

infinity, t approaches zinfinity, t approaches z For small N distribution For small N distribution

of sample variance is of sample variance is skewedskewed

Df = Df = NN-1-1

N

XXz

Xz

XX /

Ns

X

s

Xt

s

Xt

XX /


The t-testThe t-test

Differences in means of matched samplesDifferences in means of matched samples

Differences in means of Independent Differences in means of Independent samplessamples


Specialized Research DesignsSpecialized Research Designs

Combining between-subjects and within-subjects Combining between-subjects and within-subjects factors in research design – mixed designsfactors in research design – mixed designs

Combining experimental and correlational designs Combining experimental and correlational designs (Analysis of covariance or ANCOVA)(Analysis of covariance or ANCOVA)

Quasi-Experimental DesignsQuasi-Experimental Designs Pretest-posttest designsPretest-posttest designs Developmental designs (Longitudinal or cross-Developmental designs (Longitudinal or cross-

sectional)sectional)


Combining Experimental and Combining Experimental and Correlational DesignsCorrelational Designs

Covariates in experimental designsCovariates in experimental designs Measure your subjects on a Measure your subjects on a covariatecovariate—a variable that you —a variable that you

believe may be correlated with your dependent variablebelieve may be correlated with your dependent variable If left unmeasured these covariates add error variance If left unmeasured these covariates add error variance

and might obscure significant effectsand might obscure significant effects Measuring the covariate allows you to use correlational Measuring the covariate allows you to use correlational

statistical techniques in your analysis (e.g., Analysis of statistical techniques in your analysis (e.g., Analysis of Covariance or ANCOVA) to “subtract out” the error Covariance or ANCOVA) to “subtract out” the error variance associated with the covariate, thereby increasing variance associated with the covariate, thereby increasing the statistical power of your experimentthe statistical power of your experiment

Example: measuring IQ in a learning experimentExample: measuring IQ in a learning experiment


Combining Experimental Combining Experimental and Correlational Designsand Correlational Designs Quasi-independent variable in experimental designsQuasi-independent variable in experimental designs

““Quasi” means “kind of, but not really”Quasi” means “kind of, but not really” Similar to including a covariate, except Similar to including a covariate, except

measurement of covariate is used to assign Ss measurement of covariate is used to assign Ss to groups to groups

Covariate is thus treated as an quasi-Covariate is thus treated as an quasi-independent variableindependent variable

Quasi-independent variables are referred to as Quasi-independent variables are referred to as “quasi” because they cannot be manipulated, “quasi” because they cannot be manipulated, they are essentially dependent variables they are essentially dependent variables (measures) that are (measures) that are treated treated as independent as independent variables in the experimental design and analysisvariables in the experimental design and analysis


Quasi-experimental DesignsQuasi-experimental Designs

Quasi-experimental designs are those in which only quasi-Quasi-experimental designs are those in which only quasi-independent variables are usedindependent variables are used

Time series vs. pretest-posttest designsTime series vs. pretest-posttest designs Time series: Measure behavior Time series: Measure behavior several timesseveral times prior to prior to

and following a treatment (and following a treatment (time series designtime series design) or ) or change in your quasi-independent variable (change in your quasi-independent variable (interrupted interrupted time series designtime series design))

Pretest-posttest: Measure behavior Pretest-posttest: Measure behavior once once prior to and prior to and once once following the change in your independent variablefollowing the change in your independent variable


Quasi-experimental DesignsQuasi-experimental Designs

Equivalent time samples designEquivalent time samples design Time-series design especially useful for Time-series design especially useful for

treatments with transient effectstreatments with transient effects Repeatedly measure behavior following multiple Repeatedly measure behavior following multiple

applications and withdrawals of the treatmentapplications and withdrawals of the treatment Non-equivalent control group designs – helps Non-equivalent control group designs – helps

control for history confounds which should affect control for history confounds which should affect both groups equallyboth groups equally


Developmental DesignsDevelopmental Designs

Used to assess changes in behavior related to a person’s Used to assess changes in behavior related to a person’s chronological agechronological age, which serves as a quasi-independent variable, which serves as a quasi-independent variable

Cross-sectional designsCross-sectional designs Simultaneously test subjects assigned to two or more age groupsSimultaneously test subjects assigned to two or more age groups Generational effects can confound the age variableGenerational effects can confound the age variable

Longitudinal designsLongitudinal designs Repeatedly test a single group of subjects over timeRepeatedly test a single group of subjects over time Controls for generational effects—but, may still limit external Controls for generational effects—but, may still limit external

validity validity May be confounded by history, mortality, and/or multiple May be confounded by history, mortality, and/or multiple

observation effectsobservation effects Cohort-sequential designCohort-sequential design

Combines longitudinal and cross-sectional designs by measuring Combines longitudinal and cross-sectional designs by measuring multiple age groups over time which allows evaluation of multiple age groups over time which allows evaluation of generational or historical confoundsgenerational or historical confounds


Single Subject Research Single Subject Research DesignsDesigns

Research that focuses on identifying Research that focuses on identifying functional relationships between variables and functional relationships between variables and performance of a single subject (e.g., performance of a single subject (e.g., behavioral analysis and psychophysics)behavioral analysis and psychophysics)

Typically involveTypically involve Large number of observationsLarge number of observations Rigid experimental controlRigid experimental control Investigations of powerful variables whose Investigations of powerful variables whose

effects are easily detectedeffects are easily detected


Baseline DesignsBaseline Designs

Same as time-series designSame as time-series design Time series: Measure Time series: Measure

behavior behavior several timesseveral times prior prior to and following a treatment to and following a treatment

Two phases (A and B)Two phases (A and B) A: baseline phase to establish A: baseline phase to establish

behavioral baselinebehavioral baseline performance on DV prior to performance on DV prior to treatment, requires that a treatment, requires that a stability criterion stability criterion be reachedbe reached

B: intervention phase that B: intervention phase that measures performance on DV measures performance on DV after treatmentafter treatment


Baseline Reversal DesignsBaseline Reversal Designs

Problem: Time Problem: Time confoundconfound

Solution: ABA Design—Solution: ABA Design—reverse the treatment reverse the treatment by removing it and see by removing it and see if performance returns if performance returns to baseline (unlikely to to baseline (unlikely to occur by coincidence)occur by coincidence)

Problem with reversal: Problem with reversal: now behavior is at now behavior is at baseline againbaseline again

Solution: ABAB designSolution: ABAB design A B A B


Multiple Baseline DesignsMultiple Baseline Designs

Used to assess Used to assess irreversible changes in irreversible changes in behaviorbehavior

Assess multiple Assess multiple independent behaviors independent behaviors and introduce treatment and introduce treatment to only one behavior at a to only one behavior at a timetime

Controls for time effects Controls for time effects (history, maturation)(history, maturation)


Discrete Trials Designs Discrete Trials Designs (Psychophysical Techniques)(Psychophysical Techniques)

Used to determine thresholds and difference Used to determine thresholds and difference thresholds (just-noticeable differences or JNDs)thresholds (just-noticeable differences or JNDs)

Ss receive dozens or hundreds of trials under Ss receive dozens or hundreds of trials under tightly controlled conditionstightly controlled conditions

MethodsMethods Method of Constant StimuliMethod of Constant Stimuli Method of AdjustmentMethod of Adjustment Method of LimitsMethod of Limits


Classical Psychophysical MethodsClassical Psychophysical Methods

Fechner’s Fechner’s Elements of Elements of PsychophysicsPsychophysics (1860)(1860)

Absolute threshold Absolute threshold (limen): how much (limen): how much energy must exist energy must exist in a stimulus for it in a stimulus for it to be detectable?to be detectable? Subliminal: below

threshold

Superliminal: above threshold

0 20 40 60 80 100

0.5

1

Amount of Stimulus Energy

Pro

babi

lity

of

Det

ecti

on

P abs( )50

P real( ),50 10

.10 P T( ),50 10

E

Amount of Stimulus Energy

Predicted byabsolute threshold

Distribution of “absolute” threshold

Pro

babi

lity

of

Det

ecti

on

“Real World”0.5

1.0


Methods for Determining ThresholdsMethods for Determining Thresholds

Method of adjustmentMethod of adjustment Intensity or feature of stimulus is Intensity or feature of stimulus is

changed until it matches a changed until it matches a standardstandard

Hysteresis requires both ascending Hysteresis requires both ascending and descending trialsand descending trials

Average match across ascending Average match across ascending and descending determines and descending determines thresholdthreshold

Fast, but least accurateFast, but least accurate



Method of Limits (discrete method of Method of Limits (discrete method of adjustment)adjustment) Like method of adjustment except Like method of adjustment except

adjustment is done in discrete steps adjustment is done in discrete steps whose size is controlled by the whose size is controlled by the experimenterexperimenter

Hysteresis requires both ascending and Hysteresis requires both ascending and descending trialsdescending trials

Average match across ascending and Average match across ascending and descending determines thresholddescending determines threshold

Variant: Staircase methodVariant: Staircase method



Method of Constant Method of Constant StimuliStimuli Choose 5-9 stimuli, Choose 5-9 stimuli,

some above, some some above, some below thresholdbelow threshold

Present in random Present in random orderorder

threshold equals threshold equals amount of stimulus amount of stimulus energy that detected energy that detected 50% of the time50% of the time

Slowest but most Slowest but most accurateaccurate

For all Methods: For all Methods: sensitivitysensitivity = 1/threshold = 1/threshold

Amount of Stimulus EnergyP

roba

bili

ty o

f D

etec

tion

Threshold

0.5

1.0


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PSYC512: Research Methods PSYC512: Research Methods Lecture 15 Brian P. Dyre University of Idaho.

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