Chapter 9-13

Question 1

The majority of survey research is conducted to

Answer 1

answer descriptive or predictive

Question 2

when might a survey answer a causal question

Answer 2

This researcher might conduct an experiment to compare the therapies* effect on scores from a depression questionnaire, such as the Beck Depression Inventory

Another example of experiments that involve surveys is in testing the effect of new products on consumer behaviors and attitudes.

Question 3

Descriptive Research Question:

Answer 3

a search question that asks about the presence of behavior, how frequently it is exhibited, or whether there is a relationship Between different behaviors

Question 4

Predictive Research Question:

Answer 4

a research question that asks if one behavior an be predicted from another behavior to allow predictions of future behavior

Question 5

Causal Research Question:

Answer 5

a research question that asks what causes specific behaviors to occur

Question 6

Psychometrics:

Answer 6

area of psychological research that involves the development, validation, and refinement of surveys and tests for measuring psychological constructs

Question 7

There are two good sources for standardized questionnaires that may contain the type of survey you are looking for

Answer 7

• One is called the Health and Psychosocial Instruments (HAPI) database.
• The other source is called the Mental Measurements Yearbook (also available through EBSCO if you have access to that database).

Question 8

why is it important to write questions carefully, and what are the steps through which you do so?

Answer 8

• Hence, it is important to write questions carefully so as to reduce bias in responses.
  
  • Consider whether participants are able to recall the behaviors you are asking about
  • Consider how your participants perceive the question
  • Avoid double-barreled questions that are actually two questions in one
  • In addition, avoid loaded questions that assume too much

Question 9

types of survey response scales

Answer 9

open ended and close ended

Question 10

writing close ended question responses

Answer 10

• Consider how your participants view the response choices Vou provide
• Will the response categories be confusing to your participants or bias the way they respond?
• Consider the number of response categories provided to the participants.
• more response options allow for more variable responses, which can increase the validity of the scores
• Also, consider that the use of ordinal response scales, such as those described above, may not provide choices that match the participants* exact behavior
  
  • Thus, an open-ended ratio scale that allows participants to report the exact number of hours of TV they watch per day may be accurate.
• Include equal numbers of positive and negative response categories.

Question 11

construct validity

Answer 11

• Construct Validity: indicates that a survey measures the behavior it is designed to measure
• It is very important that they write survey items carefully to ensure that they address the behaviors that they intend to measure

Question 12

nonresponse as a type of coverage error

Answer 12

• nonresponse Error: a sampling error that occurs when individuals chosen for the sample do not respond to the survey, biasing the sample
  
  • Nonresponse errors are a particular type of coverage error that occurs when the sample completing the survey does not represent the entire population that the researchers wish to use to generalize the scores.
• Coverage errors reduce the external validity of your survey

Question 13

criterion related validity

Answer 13

• determining the validity of the scores of a survey by examining the relationship between the survey scores and other established measures of the behavior of interest
  
  • Often, a researcher tests the criterion-related validity of a survey to determine if the survey can predict other behaviors.

Question 14

social desirability bias

Answer 14

bias created in survey responses from respondents’ desi re to be viewed more favorably by others. Typically resulting in overreporting of positive” behaviors and underreporting of negative” behaviors

Question 15

how do researchers deal with social desirability bias

Answer 15

• include a measure of this bias such as the Marlowe-Crowne social desirability scale.
• These measures include items designed to test a respondent’s level of social desirability in order to allow a measurement of the bias within the sample

Question 16

how do Unreliable surveys reduce the validity of the scores of a study

Answer 16

• • If participants respond to the questions in a different way at different times or respond in different ways :o different sets of similar questions in the survey* the researcher is unable to draw accurate conclusions from the survey responses.

Question 17

length of survey and reliability

Answer 17

• One way to increase the reliability of scores on a survey is to use a longer survey
  
  • Shorter surveys tend to be less reliable, because an unusual response on a single item can skew the results quite a bit

Question 18

test retest reliability

Answer 18

• Test-Retest Reliability; indicates that the scores on a survey wilI be similar when participants complete the survey more than once; means that the scores on a measure are consistent over time
  *

Question 19

why is test-retest problematic

Answer 19

Getting the same participants to take a questionnaire twice can be problematic for two reasons:

participants may not come back the second time, and the sample size is then reduced-an issue known as attrition/mortality

having participants take the same questionnaire more than once can change their results through testing effects-these occur when taking a test or questionnaire once affects future scores on the scale

In addition, there may be occasions when researchers expect to find changes in scores over time based on changes in personality or attitudes as individuals develop or events that individuals experience (e.g., starting a new job, getting married) between testings.

Question 20

internal consistency

Answer 20

Internal consistency of scores indicates how similar scores on the different items of a survey are compared to one another. This is another means of evaluating the reliability of the scores on a survey

Question 21

split half reliability

Answer 21

• The items on the questionnaire are split into two halves or sections and the Relationship between the scores on the two sets of items is tested.
  
  • This is called split-half reliability- If a strong, positive relationship exists between the scores on the two sets of items, then the questionnaire has good split-half reliability
  • The advantage of split-half is that you can test the reliability with a single testing of a group of participants

Question 22

cronbach’s alpha

Answer 22

• Another method of testing the internal consistency of scores is to examine the overall correlation between pairs of items.
  
  • In other words, the relationship between the scores for each pair of terns on a survey is calculated, and then a statistical averaging of these correlations is determined for the whole survey.
  • This method is called Cronbach’s alpha (a), which is also the name of the statistical test that is used to calculate the overall correlation

Question 23

correlational studies

Answer 23

• Correlational Study: a type of research design that examines the relationships between multiple dependent variables without manipulating any of the variables
  
  • Correlational studies can also suggest the incidence or likelihood of something occurring in the presence or absence of something else.

Question 24

Correlational studies are designed to address

Answer 24

descriptive and predictive research questions.

Question 25

predictor and outcome variables

Answer 25

For correlational studies with predictive research questions, the variable that is used for the prediction is called the predictor variable, and the variable being predicted is called the outcome variable

Question 26

The goal of any correlational study is to

Answer 26

examine relationships between two or more measures of nehavior

Question 27

why does correlation not prove causation

Answer 27

This is due to the lack of manipulation of an independent variable in correlational studies and subsequent lack of control of other extraneous variables.

Question 28

Third-Variable problem:

Answer 28

the presence of extraneous factors in a study that affect the dependent variable can decrease the internal validity of the study

Question 29

manipulation of an independent variable in a study increases

Answer 29

the internal validity of the study

Question 30

The manipulation of the independent variable can occur in two ways:

Answer 30

the variable can be manipulated between subjects or within subjects.

Question 31

between subjects

Answer 31

• In between-subjects manipulations, each participant receives only one level of the independent variable.
  
  • participants are typically randomly assigned to the different levels of between-subjects variables’

Question 32

random assignment

Answer 32

• Random assignment of participants to levels allows random distribution of participant differences across the levels, making it less likely that the participants’ differences cause (and more likely that the independent variable causes) a difference across groups for the dependent variable being measured
• Random assignment is a means of controlling for participant differences across groups and increases the internal validity of the experiment

Question 33

within subjects

Answer 33

• In within-subjects manipulations, each participant receives all levels of the independent variable.
  
  • Random assignment is important for within-subjects variables in terms of the order in which participants receive the levels of the variable to control for possible order effects of the different levels of the variable.

Question 34

order effects

Answer 34

• Order Effects: occur when the order in which the participants experience conditions in an experiment affects the resu Its of the study
• Ex. If participants receive the hard copy version or the online version of the text whether the participants receive the hard copy version or the online version of the text first.
• Order effects are a particular form of testing effects, with bias occurring because of multiple testings of a participant in a study

Question 35

what is the greatest concern for between subjects experiments

Answer 35

The presence of individual differences across groups is the greatest concern for between-subjects experiments.

Question 36

when might random assignment not be sufficient in between subjects designs?

Answer 36

In I experiments where individual differences are likely to be present (such as the example about background music) and a small sample size is use d, Random assignment may not be sufficient to control for these differences.

Question 37

what shoudl ther esearcher do when random assignment is not sufficient for a between subjects experiment

Answer 37

• the researcher has two additional means of controlling for individual differences
• The first is to manipulate the independent variable as a within subjects variable* This allows participants to serve as their own controls and individual differences across groups are no longer of concern
• , the second means of control is to use a matched design for between-subjects experiments. In a matched design, participants are matched on a characteristic that may contribute to group differences. Then each participant within a matched set is randomly assigned to different groups.

Question 38

adjusting for between group differences using comparison

Answer 38

• Another way to ensure that participants in the groups are matched on some characteristic is to measure that characteristic (e.g.. Years of education, socioeconomic status, language abilities) during the experiment and then compare the groups in an additional analysis
• This comparison indicates if the groups are similar or different on that characteristic.
  
  • However, if the groups are different, you are then left with the possibility that this difference affected your results. Thus, it you are concerned that a group difference is likely to affect your results, it is best to either use a within-subjects manipulation or match your participants before you assign them to the groups.

Question 39

primary concern for within subjects designs

Answer 39

• The primary concern of within-subjects variables is the order in which the participants receive the different levels of the independent variable.
• Because the participants receive all levels of the independent variable, it is possible that the order of the levels can affect the dependent variable measure

Question 40

To solve the problem of order effects for within-subjects manipulations

Answer 40

• TO solve the problem of order effects for within-subjects manipulations, a researcher typically counterbalances the order of the levels within the study
• This means that different groups of participants receive different orders of the levels of the independent variable
• The counterbalancing for a simple factorial experiment with four conditions is very complicated. To simplify the counterbalancing in such a case, a partial counterbalancing technique, called a Latin square, can be used instead.
  
  • In a Latin square, the number of orders used in the experiment is equal to the number of conditions in the design, and each condition is in each ordinal position (i.e., first, second, third, fourth) exactly once. Latin squares can be useful for within-subjects designs where independent variables have the same number of levels.

Question 41

factorial designs

Answer 41

many experiments conducted by researchers are factorial designs, meaning they contain more than one independent variable

Question 42

advantage of factorial

Answer 42

The primary advantages of a factorial design over simpler experiments is that a researcher can be more efficient in testing the effects of multiple independent variables in one experiment and can also examine the effects of the interactions of those independent variables on the dependent variable

Question 43

main effect (factorials)

Answer 43

• In factorial designs, the comparison of means for the levels of one independent variable is the test of the main effect of that independent variable
• In other words, the main effects indicate the independent causal effect of each independent variable in a factorial design.
• The main effect is one type of effect tested in an analysis of variance (ANOVA), Which is the type of statistical analysis used most often for a factorial experiment

Question 44

interaction effects, ANOVA

Answer 44

The other type of effect tested in an ANOVA is an interaction effect he interaction effect tests the effect of one independent variable for each level of another independent variable to determine how the independent variables interact to affect the dependent variable

Question 45

simple effects tests

Answer 45

Simple Effects Tests: statistical tests conducted to characterize an interaction effect when one is found in an ANOVA

Question 46

What is an interaction between independent variables?

Answer 46

An interaction can occur between independent variables such that the effect of one independent variable depends on which level of the other independent variable one is looking at. For example, an independent variable can show a difference between levels for Level 1 of another independent variable but show no difference between levels for Level 2 of the other independent variable.

Question 47

quasi experiments

Answer 47

• a researcher often conducts a quasi-experiment, w here groups of participants are compared on a behavior of interest, as in an experiment, but the quasi-independent variable is not manipulated, which leaves the study open to other possible explanations o£ he results.
• In other words, groups that have not been randomly assigned can be compared in a quasi-experiment, but one cannot gain strong causal information, because of the lack of random assignment
• 3uasi Experiment: a type of research design where a comparison is made, as I n an experiment, but no random assignment of participants to groups occurs

Question 48

when is behavior measured in pretest post test

Answer 48

twice: once before a treatment or condition is implemented (the pretest) and once after it has been implemented (the posttest).

Question 49

why is pretest posttest quasi experimental

Answer 49

• This design is a quasi-experiment because there is no random assignment of participants to the treatment. In this case, all the participants get the treatment. The researcher compares the scores from the pretest and the posttest, looking for a change based on the treatment or condition occurring between the two measurements
• However, if a change occurs in this design, the researcher cannot automatically conclud e lat the treatment or condition caused the change because other factors (besides the treatment or condition) may have occurred as well between the two measurements

Question 50

how can researchers deal with problems of pretest posttest

Answer 50

• Researchers can attempt to deal with some of the alternative explanations in pretest- posttest designs by including a control group*.
• If participants are randomly assigned to the control group and the treatment group, the study becomes an experiment.

Question 51

pretest posttest with nonequivalent groups

Answer 51

group differences that might account for the results are not controlled by random assignment to groups

In this design, the researcher considers the difference between the pretest and posttest scores across the control and experimental groups

Question 52

regression to the mean

Answer 52

Regression toward the mean-a high score achieved at posttest may be an extreme score in some cases, and with additional testing, these students may score closer to their original mean (which is typically lower than the norm)

Question 53

regression to the mean in pretest posttest

Answer 53

Pretest-posttest designs are susceptible to bias due to regression toward the mean because one extreme score (high or low) can skew the change in scores between the pretests and posttests

One major drawback to the pretest-posttest design is that the participants are tested vice on the same behavior.

This can cause a source of bias known as testing effects. Testing effects occur when participants are tested multiple times and each subsequent test s affected by the previous tests

Question 54

solomon four group design

Answer 54

One method of evaluating testing effects in pretest-posttest studies is the use of a Solomon four-group design

In the Solomon four-group design, he pretest-posttest design with nonequivalent groups is used.

However, two sets of each roup type are included: one set that takes the pretest and posttest as illustrated in Figure 12.2 and one set that takes only the posttest to allow comparison of the two sets of groups

Comparison across the group sets Indicates if testing effects occur For example,

Solomon Four-Croup Design: pretest posttest design with two sets of nonequivalent groups, one set that takes the pretest and posttest and one set that takes only the posttest

Question 55

time series designs

Answer 55

• For some measures of behavior or attitudes, the measures may fluctuate a good deal from week to week or month to month. In these cases, a single week or month to month. In these cases, a single e true nature of the behavior. The pretest can occur at a time when scores happen to be particularly high or particularly low. Which can bias the change in scores from pretest to posttest.
• Time series designs are special pretest-posttest designs that account for these fluctuations t>y measuring the behavior or attitude multiple times before the treatment and multiple times after the treatment over the same time period.
• the patterns of scores before and after the treatment compared to determine if a difference has occurred over time.

Question 56

difference between regular pre test post test and time series designs

Answer 56

The patterns of scores are compared in a time series design, rather than two scores as in the simple pretest-posttest design.

Question 57

interrupted time series designs

Answer 57

in Interrupted time series design, the treatment is an independent event that the researchers have no control over:

events such as a war, passage of a new law, or other historical events are considered “treatments” in an interrupted time series design in that patterns of scores are compared

Archival data are used as observations in the study

Question 58

noninterrupted time series designs

Answer 58

• designs with a researcher-implemented treatment are called non interrupted time series designs.
• The behavior of interest is measured over time both before and after a treatment has been introduced

Question 59

limitations of time series designs

Answer 59

As with pretest-posttest designs, limitations of time series designs exist due to possible extraneous factors that can affect a score pattern change other than the treatment or event of interest

Question 60

sources of bias in quasi experiments

Answer 60

history effects

maturation

attrition and mortality

Question 61

history effects

Answer 61

events that occur during the course of a study to all participants or to individual participants that can result in bias

Question 62

history effects most likely to occur in

Answer 62

pretest-posttest designs

Question 63

The best way to minimize effects that occur over time in a pretest-posttest design is

Answer 63

to include a control group that takes the pretest and posttest at the same time as the experimental group but does not receive the treatment given to the experimental group

Question 64

maturation and best way to minimize it

Answer 64

Maturation occurs when participants exhibit natural changes over the course of a study

He best way to minimize f fects of maturation is to include a control group that does not receive the treatment to allow a compariso n )f groups that have similar experiences except for the treatment.

Question 65

attrition

Answer 65

Attrition (also called mortality) occurs when participants drop out of a study after completing only part of the study

Question 66

developmental designs

Answer 66

There are three main types of developmental designs ) that treat the factor of age in a different way: longitudinal designs, cross-sectional designs, and cohort-sequential designs

Question 67

longitudinal design

Answer 67

Longitudinal designs treat age as a within-subjects variable

Participants are tested at different ages in their lives

Question 68

how is longitudinal design considered within subjects?

Answer 68

• Participants are tested at different ages in their lives
• ‘This is how age is considered a within-subjects variable in the longitudinal design, although age is not an independent variable in this case because age cannot be manipulated.

Question 69

disadvantages of longitudinal designs

Answer 69

• One of the disadvantages of the longitudinal design: It takes time to wait for the participants to age.
• Another disadvantage is that attrition/ mortality (i.e., some participants do not complete the study) may occur over time as the study is conducted
• A third disadvantage is that testing effects can occur with multiple testings of the same participants.
  
  • In other words, being tested on the measures early in the study can affect the later testings, as participants scores can show effects of practice or fatigue

Question 70

cross sectional designs

Answer 70

• Developmental designs that treat age as a between-subjects variable are called cross-sectional designs.
  
  • These designs compare different age groups of participants, where each participant contributes data for only one age group
  • The cross-sectional design solves many of the problems that can occur with longitudinal designs.

Question 71

advantages of cross sectional designs

Answer 71

• Each participant is tested only once, which reduces the chance of attrition.
• In addition, because the researcher collects data from all age groups at he same time, the study can be completed more quickly with a cross-sectional design.

Question 72

disadvantages of cross sectional

Answer 72

• However, there are some drawbacks to the cross-sectional design that are more problematic :han in longitudinal designs.
• For example, if the age groups being tested contain participants om different generations, generation effects (also called cohort effects) might affect the results
• These effects occur when the experiences of one generation (e.g., growing up with or without computers) are very different from those of another generation and affect the way the participants complete the task or measure in the study

Question 73

cohort sequential design

Answer 73

• The third type of developmental design combines elements or tne longitudinal and cross sectional designs.
• In a cohort-sequential design, age is treated as both a between-subjects and within-subjects factor.
• Cohort-sequential designs begin with separate samples of different they develop to allow participants to be tested at multiple ages, as in a longitudinal design.

Question 74

small n designs

Answer 74

• These designs are sometimes called single-subject or single-case designs, but they often include more than one participant: thus, small n is a better descriptor of this design type
• The goal of a small-n study is to understand an individual’s behavior, either to better describe the behavior as it occurs for many individuals or in order to change that behavior.

Question 75

difference between small n and case study

Answer 75

this design is different from a case study in that the goal of a case study is to explore an individual’s behavior when little is known about the behavior.

Question 76

what is typically being tested in small n designs

Answer 76

In a small-n design, a researcher is typically testing a theory about how a behavior works for most individuals or testing a treatment for a problematic behavior of an individual or group of individuals this is accomplished through repeated measurement of behavior )

Question 77

small n baseline designs

Answer 77

baseline designs, where the repeated measurement of the baseline behavior of one or a few participants is compared with their behavior during the implementation of a treatment

Involve experimental comparison of baseline Behavior and behavior with a treatment.

The goal is to determine if a treatment creates a desired change in the behavior of interest (often an undesirable behavior), a technique also called behavior modification

A-B-A design or reversal design

Question 78

small n discrete trials designs

Answer 78

discrete trials designs, where one or a few participants complete a large number of trials of a task to describe how performance on the task operates

Discrete Trials Design: a sma I l-n design that involves a large number of trials completed by one or a few individuals and conducted to describe basic behaviors

With the controls used in an experiment and the large amount of data collected under these conditions, discrete trials designs allow for good tests of causal relationships for behaviors where there are few individual differences.

Thus discrete trials designs tend to achieve stable measures of behavior with high internal validity.

Mathematical description of behavior is often a common goal of discrete trials designs

Question 79

advantages of small n designs

Answer 79

• The primary advantage of small-n designs comes from the large number of observations collected from one or a few participants.
• Using a large number of observations reduces the error in the data (seen in the low variability of the scores) and makes it easier for a researcher to detect an effect of an independent variable.
• Using a small number of participants also makes it easier for a researcher to control for extraneous factors that may bias the data.
• This control increases the internal validity of the study

Question 80

disadvantages of small n designs

Answer 80

• The main disadvantage to small-n designs is that the results cannot always be generalized to people outside the study
• This is why they are typically used to study very basic behaviors (eg., sensory processes, learning processes), where the behaviors being measured should be very similar from person to person, and for studies where the goal is to tailor a treatment to a specific person.
• In addition, small-n designs cannot be used to measure many types of behavior.
• Due to the large number of observations collected, carryover effects can occur for tasks that may affect future performance over time.
• In other words, participants experiences in the treatment condition can affect their later behavior in a second baseline condition that the follows the condition treatment

Question 81

A-B-A design or reversal design

Answer 81

• the baseline measure of behavior (designated as Condition A) is first taken
  
  • Then the treatment (designated as Condition b) is implemented, and behavior is measured again, this time with the treatment.
  • Finally* a baseline measure (A) is made again after the treatment has been stopped to determine if the baseline behavior appears once again after the treatment has been stopped
  • % A common variant of this procedure is the A-B-A-B design, where the treatment is then implemented a second time to determine if the behavior still changes with implementation of the treatment.

Question 82

Data Analysis in Small-n Designs

Answer 82

• Because there are no group means to present in small-n designs, data are often presented for the individual participants in the study (with no identifying information to protect their confidentiality)
• Inferential statistics are sometimes reported for discrete trials designs for within-subjects variables that are manipulated in these types of designs.
• Inferential statistics can only be used in baseline designs if a large number of observations are collected for each individual.