Exam 3 Questions

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20. (8` points) Two observers observe a child in the classroom every 30 minutes to record whether he is behaving aggressively. They use two categories for their observations: yes (aggressive) or no (not aggressive). Using the data presented below, answer the following question.  

Calculate and report the observers’ interobserver reliability.

Do you think the observers demonstrated acceptable interobserver reliability? Why or why not?

21. (5 points) A researcher was interested in determining whether more frequent breaks (i.e., “coffee breaks”) in a business setting would help employees to be more productive. With the cooperation of the management, employees on one floor of the corporate offices were allowed to take a 10-minute break each hour (at any time) between 8:00 and 11:00 A.M. (for a total of 30 minutes). The comparison group comprised employees on different floors who followed the usual corporate policy of taking a 30-minute break sometime during the morning (at any time). Measures of productivity were gathered for each employee according to his or her job (e.g., number of reports written, number of sales made, etc.). A time series analysis was applied to compare the productivity of both groups of employees for six months before and after the intervention (started in July). Quite surprisingly, the productivity of both groups increased following the onset of the intervention, suggesting to the researcher that the timing of breaks makes no difference.

What type of research design was used in this study?

Describe two ways in which contamination may have influenced the results of this study.

Describe one threat to internal validity that might be present in this study because the independent variable manipulation was implemented on different floors of the building.

Research Methods in Psychology

Quasi-Experimental Designs


Characteristics of True Experiments

Manipulate Independent Variable (IV)

Treatment, comparison conditions

High degree of control

Choice of the DVs

Random assignment to conditions

Unambiguous outcome regarding effect of IV on DV

Internal validity


Applied Research


Test external validity of lab findings

Improve conditions in which people live and work (natural settings)


Procedures that approximate the conditions of highly controlled laboratory experiments



Difficult to gain permission to conduct true experiments in natural settings

Difficult to gain access to participants

Random assignment perceived as unfair

People want a “treatment”

Random assignment is best way to determine whether a treatment is effective

Use “waiting-list” control group or alternate treatments

Tablets in English and science classes example

Obstacles to Conducting True Experiments in Natural Settings


Advantage of True Experiments

Threats to internal validity are controlled

8 general threats to internal validity

history regression
maturation selection
testing subject attrition
instrumentation additive effects with selection


Threats to Internal Validity


When an event occurs at the same time as the treatment and changes participants’ behavior

Participants’ “history” includes events other than treatment

Difficult to infer treatment has an effect


History Threat, continued

Does a campus recycling awareness campaign influence the amount of paper, plastic, and cans in campus bins?

History threat: Suppose at week 4 (X = treatment) a popular celebrity also starts to promote recycling in the media.

Can you conclude the campus campaign was effective?


Series 1 1 2 3 4 X 5 6 7 8 30 35 30 35 40 55 55 60 55Week

Recycling (Kg)

Threats to Internal Validity, continued


Participants naturally change over time.

These maturational changes, not treatment, may explain any changes in participants during an experiment.


Maturation Threat, continued

Does a new reading program improve 2nd graders’ reading comprehension?

Reading comprehension improves naturally as children mature over the year.

Can you conclude the reading program was effective?


Series 1 Pre Post 25 70Reading Comprehension

Threats to Internal Validity, continued


Taking a test generally affects subsequent testing.

Participants’ performance on a measure at the end of a study may differ from an initial testing because of their familiarity with the measure.


Testing Threat, continued

Does teaching a new problem solving strategy influence people’s ability to solve problems quickly?

If similar problems are used in the pretest, faster problem solving at post-test may be due to familiarity with the test.

Can we conclude the new strategy improves problem-solving ability?


Series 1 Pre Post 12 4Minutes (Mean)

Threats to Internal Validity, continued


Instruments used to measure participants’ performance may change over time

Example: observers may become bored or tired

Changes in participants’ performance may be due to changes in instruments used to measure performance, not to a treatment.


Instrumentation, continued

Suppose a police protection program is implemented to decrease incidence of assault.

At the same time the program is implemented (X), reporting laws change such that what constitutes assault is broadened.

Can we conclude the program was effective (or ineffective)?


Series 1 1 2 3 4 X 5 6 7 8 25 20 22 24 35 45 40 35 38 Series 2 1 2 3 4 X 5 6 7 8 Series 3 1 2 3 4 X 5 6 7 8Week


Threats to Internal Validity, continued


Individuals sometimes perform very well or very poorly because of chance (e.g., luck).

Chance factors are not likely present during 2nd testing, so scores will not be as extreme.

Scores will “regress” (go toward) the mean.

Regression effects, not treatment, may account for changes in participants’ performance over time.


Regression, continued

Suppose students are selected for an enrichment program because of their very high scores on a brief test.

Regression: to the extent the test is an unreliable measure of ability, we can expect their scores to regress to the mean at the 2nd testing.

Can we conclude the enrichment program was effective (or ineffective)?


Series 1 Pre Post 90 70Test Score (Mean)

Threats to Internal Validity, continued

Subject attrition

When participants are lost from the study (attrition), the group equivalence formed at the start of the study may be destroyed.

Differences between treatment and control groups at the end of the study may be due to natural differences in those who remain in each group.


Subject Attrition, continued

Suppose an exercise program is offered to employees who would like to lose weight.

At Time 1, N = 50

M weight = 225 pounds

At Time 2, N = 25 (25 drop out of study)

Suppose the 25 who stayed in program weighed, on average, 150 pounds at Time 1

Did the exercise program help people to lose weight?


East Time1 Time2 0 225 150 0MeanWeight

Threats to Internal Validity, continued


Occurs when differences exist between individuals in treatment and control groups at the start of a study

These differences become alternative explanations for any differences observed at the end of the study

Random assignment controls the selection threat


Selection, continued

Suppose a community recycling program is tested. Individuals who are interested in recycling are encouraged to participate.

Evaluation: Compare the weight of garbage (i.e., not recycled) from participants in the program with weight of garbage from those not in the new program.

Can we tell if the new recycling program is effective?


East In Not In 0 15 35 0Recycle Program

mean lbs/week

Threats to Internal Validity, continued

Additive effects with selection

When one group of participants in an experiment

Responds differently to an external event (history)

Matures at a different rate

Is measured more sensitively by a test (instrumentation)

These threats (rather than treatment) may account for any group differences at the end of a study.


Additive effects with selection, continued

Suppose School A starts a program (X) to prevent alcohol abuse on campus (Week 4). The DV is number of alcohol-related infractions in student residences.

School B is a comparison.

During Week 4 the newspaper at School A reports a student death due to intoxication (“local history effect”).

Is the program effective?

School A 1 2 3 4 X 5 6 7 8 9 8 8 9 1 3 2 3 2 School B 1 2 3 4 X 5 6 7 8 8 10 9 7 8 7 10 9 9 Column1 1 2 3 4 X 5 6 7 8Week

# Infractions

Threats to Internal Validity, continued

With no comparison group, must rule out:

history, maturation, testing, instrumentation, regression, subject attrition, selection

When there is a comparison group, you must rule out these threats:

selection, additive effects with selection

Adding a comparison group helps rule out many threats to internal validity.


Stretching Exercise, page 323

Threats to Internal Validity, continued

Threats even true experiments may not eliminate


resentment, rivalry, diffusion of treatments

Experimenter expectancy effects

Novelty effects (including Hawthorne effect)

Threats to external validity

Treatment effects may not generalize

Best way to assess external validity: replication



“Quasi-” (resembling) experiments

Important alternative when true experiments are not possible

Lack the high degree of control found in true experiments

Often no random assignment

Researchers must seek additional evidence to eliminate threats to internal validity


The One-Group Pretest-Posttest Design

“Bad experiment” or “pre-experimental design”

Intact group is selected to receive a treatment

e.g., a classroom of children, a group of employees

Pretest is 1st Observation (O1)

Treatment is implemented (X)

Posttest is 2nd Observation (O2)

O1 X O2


One-Group Pretest-Posttest Design, cont.

O1 X O2

None of the threats to internal validity are controlled.

Any change between pretest (O1) and posttest (O2) may be due to treatment (X) or




Or instrumentation, regression, subject attrition, selection


Quasi-Experimental Designs

Nonequivalent Control Group Design

A group similar to the treatment group serves as a comparison group

Obtain pretest and posttest measures for individuals in both groups

Random assignment to groups is not used

Pretest scores are used to determine whether the groups are equivalent

Equivalent only on this dimension


Nonequivalent Control Group Design, continued

O1 X O2 ← treatment group
O1 O2 ← nonequivalent control group
pretest posttest

Nonequivalent Control Group Design, continued

Example: Does taking a research methods course improve reasoning ability?

Compare students in research methods and developmental psychology courses

DV: 7-item test of methodological and statistical reasoning ability

Suppose group differences are observed at the posttest


Nonequivalent Control Group Design, continued

By adding a comparison group, rule out these threats to internal validity:






Assume that these threats happen the same to both groups, therefore, can’t be used to explain posttest differences.


Methods Pre Post 3 5 Developmental Pre Post 2.5 2.75Mean Reasoning Score

Nonequivalent Control Group Design, continued

What threats are not ruled out?


Without random assignment to conditions, the two groups are probably not equivalent on many dimensions.

These preexisting differences may account for group differences at the posttest.


Nonequivalent Control Group Design, continued

Additive effects with selection

The two groups

May have different experiences (selection X history or “local history effect”)

May mature at different rates (selection X maturation)

May be measured more or less sensitively by the instrument (selection X instrumentation)

May drop out of the study (courses) at different rates (differential subject attrition)

May differ in terms of regression to the mean (differential regression)


Quasi-Experiments, continued

Simple Interrupted Time Series Design

Observe a DV for some time before and after a treatment is introduced.

Archival data are often used.

Look for clear discontinuity in the time-series data for evidence of treatment effectiveness.

O1 O2 O3 O4 X O5 O6 O7 O8


Simple Interrupted Time-Series Design, cont.

Example: Study habits

Intervention: An instructional course to change students’ study habits

Implemented during summer following the sophomore year (after semester 4)

DV: semester GPA

Suppose a discontinuity is observed when the treatment (X) is introduced


Simple Interrupted Time-Series Design, cont.

What threats can be ruled out?

Maturation: assume maturational changes are gradual, not abrupt

Testing (GPA): if testing influences performance, these effects are likely to show up in initial observations (before X)

Testing effects less likely with archival data

Regression: if scores regress to the mean, they will do so in initial observations



Series 1 1 2 3 4 5 6 7 8 1.9 2 1.75 2 3 3.25 3 3.5Semester

Mean GPA

Quasi-Experiments, continued

Time Series with Nonequivalent Control Group Design

Add a comparison group to the simple time-series design

O1 O2 O3 O4 X O5 O6 O7 O8


O1 O2 O3 O4 O5 O6 O7 O8


Time Series with Nonequivalent Control Group Design, continued

Example: Study habits

Suppose a nonequivalent control group is added—these students don’t participate in the study habits course

Who could be in the comparison group?

What threats would you be able to rule out?


Treatment 1 2 3 4 5 6 7 8 1.9 2 1.75 2 3 3.25 3 3.5 Control 1 2 3 4 5 6 7 8 2 1.9 2.1 2 2 2.1 2.25 2Semester

Mean GPA

An Example

Study to determine if well being is increased if nursing home residents are given the opportunity to make daily personal decisions (how their room is arranged, visits, movie choices)

Two groups: choice group and no-choice group

Assignment to groups was done by floor in a nursing home

These floors were chosen due to similarity in the residents’ physical and psychological health and prior SES

Questionnaires administered 1 week before and three weeks into the study

Staff members rated residents before and after treatment (alertness, sociability, and activity)

Contest—guess the number of jelly beans in a jar.

What is the independent variable?

What is/are the dependent variable(s)?

What type of quasi-experimental design?

Which threats to internal validity are controlled?

Which threats are not controlled?

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