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CPCE > Research > Flashcards

Research Flashcards

1
Q

quasi-experiment

A

uses preexisting groups
the IV cannot be altered (ex: gender or ethnicity)
you cannot state that the IV caused the DV
an example of a quasi-experimental study: ex post facto

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2
Q

regression

A

or statistical regression

extremely high and low scores will regress toward the mean if the measure is given again

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3
Q

internal validity

A

whether the DVs were truly influenced by the experimental DVs or whether other factors had an impact (confounding factors/contaminating variables/extraneous variables)

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4
Q

external validity

A

generalizability

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5
Q

parsimony

A

the best explanation is the easiest and least complex

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6
Q

Occam’s Razor

A

synonymous with parsimony
interpret the results in the simplest manner
no matter the study, there will be flaws. minimize the worst ones
(car windshield sticker, bubbles)

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7
Q

all correlational research is said to be ____

A

confounded

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8
Q

1 periodical for research

A

APA’s Journal of Counseling Psychology

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9
Q

basic research

A

conducted to advance our understanding of theory

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10
Q

applied research

A

conducted to advance out understanding of how theories, skills, and techniques can be used in terms of practical application
AKA action research or experience-near research

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11
Q

IV vs DV

A

I manipulate the IV

DV is the Data our outcome

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12
Q

casual-comparative design

A

a true experiment except for the fact that groups were not randomly assigned; so you didn’t truly control the IV
data gleaned from the casual comparative can be analyzed with a test of significance (e.g. t-test or ANOVA) just like any true experiment

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13
Q

DV must be ____ measured

A

that which is directly measured
ex: you hypothesize that biofeedback will reduce anxiety and increase test scores. the DV is test scores because you’re not measuring anxiety in the experiment.

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14
Q

You need ___ participants for a true experiment

A

30

15 in control group, 15 in experimental group

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15
Q

Surveys need ___ people with a response rate of at least ____.

A

100 people

50-75%

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16
Q

organismic variable

A

a variable the researcher cannot control/manipulate, yet exists such as height, weight, gender
AKA status variable

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17
Q

___ pioneered hypothesis testing

A

R. A. Fisher

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18
Q

The null hypothesis states that

A

the IV does not affect the DV

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19
Q

experimental hypothesis

A

your hunch, that the IV does affect the DV

AKA affirmative hypothesis

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20
Q

t-test

A

used to determine if a significant difference between 2 means exists (on one variable)
find the “critical t” in a table
if your t value is above it, then you reject the null
if your t is below it, then you accept the null

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21
Q

between-subjects design vs. within-subjects design

A

between-subjects - uses different subjects for each condition
within-subjects - same subjects are studied (e.g., get a pre- and post-test after administering the IV)

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22
Q

parameter

A

a value obtained from a population

vs. statistic - a value drawn from a sample

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23
Q

P represents

A

probability or the level of significance

AKA alpha level

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24
Q

in research, P should be set at ___

A

P = .05 or lower
(e.g. .01, .001)
P = significance level
.05 might be referred to as “95% confidence interval”

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25
Q

A significance level of .05 means

A

the differences observed would occur via chance only 5 times out of 100
the probability of committing a Type I or alpha error is .05

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26
Q

the 95% confidence interval means

A

P = .05

the differences observed would occur via chance only 5 times out of 100

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27
Q

alpha error

A

AKA Type I error
When the researcher rejects the null when it is true
The probability of committing a Type I error is the level of significance

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28
Q

beta error

A

AKA Type II error

When the researcher accepts the null hypothesis when it is false

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29
Q

power of a statistical test =

A

1 - beta

power means the test’s ability to correctly reject the null hypothesis

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30
Q

think of Type I and II errors like

A

a seesaw

the risk of committing one error goes up when the other goes down

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31
Q

how to lower the risk of chance/error factors

A

increase the sample size

differences revealed via large samples are more likely to be genuine than differences revealed using a small sample size

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32
Q

ANOVA

A

use to compare the means of > 2 groups (as opposed to t-test) on one variable
the resulting value is an F-value
consult the F-value
if your F-value is higher, reject the null
if your F-value is lower, accept the null

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33
Q

positively skewed

A

mode < median < mean

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34
Q

negatively skewed

A

mode > median > mean

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35
Q

kurtosis

A

peakedness of a distribution

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36
Q

kurtosis - types

A

leptokurtic - peaked
mesokurtic - normal
platykurtic - no peak, flat

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37
Q

dependent t-test

A

t-test where 2 similar groups are matched in some meaningful way, or the same group is tested twice

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38
Q

independent t-test

A

comparing 2 independent groups (that are usually assigned randomly) on one variable
independent groups might also be called unmatched/uncorrelated

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39
Q

a test for more than one IV and more than 2 groups

A

factorial ANOVA
Ex: if two treatments CBT and interpersonal therapy [IPT] are compared for effectiveness on males and females and different treatments were significantly more
effective with different genders—for example, CBT worked significantly better for males than females while IPT worked significantly better for females than males).

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40
Q

a test for more than one IV, more than 2 groups, where you want to control one of the IV’s

A

analysis of covariance
ANCOVA
e.g., examining the relationship between household income and work satisfaction, with gender as a covariate—that is, the statistical effects of gender are removed from the
analysis to control for any effects gender might have on work satisfaction

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41
Q

a test for more than one IV, more than 2 groups, and more than one DV

A

MANOVA (multiple)

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42
Q

a test for more than one IV, more than 2 groups, and more than one DV, controlling for one IV

A

MANCOVA (multiple)

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43
Q

parametric statistics

A

rely strictly on interval and ratio data
parametric tests are used when the following assumptions are met:
1. Data for the dependent variable(s) are approximately normally distributed.
2. Samples were randomly selected and/or assigned.
3. An interval or ratio scale of measurement was used for each of the variables involved in the study.
ex: t-test, ANOVA, factorial ANOVA, ANCOVA, MANOVA, MANCOVA

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44
Q

non-parametric statistics

A

used when we can’t make assumptions about distribution of true scores in the population like we can when we use parametric statistics
suggested when nominal or ordinal data are involved or when interval or ratio data are not distributed normally (i.e., are skewed).
ex: chi-square, Mann-Whitney U test, Kolmogorov-Smirnov Z procedure, Kruskal-Wallis test, Wilcoxon’s signed-ranks test, Friedman’s rank test

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45
Q

the non-parametric version of the ANOVA

A

Kruska-Wallis test
(so this will be an extension of the Mann-Whitney U-Test when there are more than 2 groups, just like the ANOVA expands the t-test)

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46
Q

the non-parametric version of the t-test when means are correlated

A

Wilcoxon’s signed-ranks test
want to test whether 2 “co-related” means differ - WilCOxon, “co”
synonymous with the dependent t-test

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47
Q

the non-parametric version of the t-test when means are uncorrelated

A

Mann-Whitney U-Test
want to test whether 2 Un-correlated means differ (U-Test, Un-correlated)
uses ordinal data instead of interval or ratio data
synonymous with the independent t-test

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48
Q

non-parametric version of Pearson’s r

A

Spearman correlation or Kendall’s tau

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49
Q

chi-square test

A

nonparametric
used with two or more categorical or
nominal variables, where each variable contains at least two categories that MUST be mutually exclusive. All scores must be independent
examines whether obtained frequencies differ significantly from expected frequencies
ex: the decision to terminate counseling (yes, no) and the gender of the professional counselor (male, female). A chi-square
would test whether the tallies for the decision to quit counseling by gender of counselor are significantly different from those expected in the population.

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50
Q

Kolmogorov-Smirnov Z procedure

A

nonparametric

use in place of Mann-Whitney U-Test when the sample size < 25

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51
Q

Friedman’s rank-test

A

Similar to Wilcoxon’s signed-

ranks test in that it is designed for repeated measures; also can be with more than two groups

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52
Q

one-way vs two-way ANOVA

A

one-way tests on IV
two-way tests two IVs

when it’s more than one DV, it’s a MANOVA

53
Q

r

A

indicates the degree or magnitude of relationship between 2 variables
correlation coefficient

54
Q

positivism

A

objective truth exists and can only be understood if directly observable

55
Q

post-positivism

A

truth can only be approximated

56
Q

constructivism

A

AKA interpretivism

there are multiple realities / truths

57
Q

critical/idealogical paradigm

A

researchers take a proactive role in confronting social structure and conditions facing oppressed or underprivileged groups

58
Q

biseral correlation

A

one variable is continuous, and the other is dichotomous

ex: correlate CPCE score to NCC status

59
Q

phi-coefficient correlation

A

when both variables are dichotomous

ex: NCC status and CCMCH status

60
Q

single-subject research designs

A

SSRDs
a type of within-series TRUE experimental design
can be with one person or a small group
often assess the effectiveness of programs for specific clients
AB (like post-test only)
ABC, etc

61
Q

Spearman rho

A

a correlation coefficient for ordinal data (rank-order)

rhO - Ordinal data

62
Q

bivariate regression

A

how well scores from an independent (predictor) variable predict the dependent variable (criterion variable)

63
Q

multiple regression

A

AKA multivariate

more than one predictor variable (IV)

64
Q

logistic depression

A

the dependent variable is dichotomous, may be similar to a bivariate or multiple regression

65
Q

effect size

A

the measure of the strength of the relationship between two variables in the population
There is an effect size for each variable in a study

66
Q

the effect size is the ____ in a meta-analysis

A

effect size

67
Q

ABCD model for developing program objectives

A 
A = audience (affected individuals)
B = behavior (expected action or attitude)
C = conditions (context in which behavior will occur)
D = description (concrete performance criteria)
68
Q

four major components of program evaluation

A

Needs assessment
Process evaluation
Outcome evaluation
Efficiency analysis (do gains outweigh costs?)

69
Q

Inductive analysis

A

the data allow notions of a phenomena (theory) to emerge
infers conclusions from data
qualitative research
specific to general

70
Q

Deductive analysis

A

starts with theory
confirms a hypothesis
quantitative research
general to specific

71
Q

focus groups include ____ members

A

include 6-12 members

72
Q

participatory action research (PAR)

A

focuses on change of the participants and the researcher as a result of qualitative inquiry; goals are emancipation and transformation
ex: working with a community agency and its clients to move toward improving the agency

73
Q

ethnography

A

qualitative research

studies the culture of a group or system

74
Q

consensual qualitative research (CQR)

A

combines phenomenology and grounded theory
researchers select participants who are very knowledgable about a topic
some hope of generalizing to a larger population
researchers reflect their own experiences when developing the interview questions
emphasis on POWER in all aspects — power is shared among researchers and participants

75
Q

grounded theory

A

qualitative research; inductive approach

purpose is to generate theory that is grounded in data from participants’ perspectives on a particular phenomena

76
Q

phenomenology

A

used to discover or describe the meaning or essense of participants’ lived experiences with the goal of understanding individual and collective human experiences for various phenomena

77
Q

non-experimental designs (AKA quasi-experimental)

A

exploratory and descriptive
no intervention
no variable or conditions are manipulated
goal is to observe and outline the properties of a variable

78
Q

types of quasi-experimental research designs

A 
descriptive design (1 variable), comparative design (>1 group, 1 variable)
correlational design (relationship between 2 variables)
ex post facto (AKA casual comparative; "after the fact" nothing was manipulated)
79
Q

coefficient of determination

A

shared variance between 2 variables
square the correlation coefficient r
e.g. r = 0.5
0.5 x 0.5 = 0.25

80
Q

ex post facto design

A

assessing whether one or more pre-existing conditions (unmanipulated IVs) possibly caused differences in groups
quasi-experimental study
conducted after the fact
randomization and manipulation cannot be achieved

81
Q

purposive sampling

A

used in qualitative research to get information-rich cases that allow for maximum depth and detail about a phenomena
AKA purposeful sampling

82
Q

trustworthiness (definition and 4 components)

A

the validity or truthfulness of a qualitative study
4 components:
credibility - is it believable
transferability
dependability - consistency over time and potential future researchers
confirmability - what you found genuinely represents participants’ views

83
Q

experimental research designs

A

involve manipulating conditions and variables
random assignment of groups is usually necessary
can be a single group

84
Q

action research

A

done by counselors in an effort to improve their own practice or organizational efficiency

85
Q

cross-sectional research

A

examines different groups or cohorts at a particular period in time, with differences in experience being compared
AKA synchronic method

86
Q

threats to external validity of a study

A

novelty affect - an exciting new treatment
experimenter effect
history by treatment effect (can’t truly replicate a study at another time period bc of particular events that happened in the world the previous time it was implemented)
measurement of the dependent variable (type of measurement may affect results)
time of measurement by treatment affect (when you administer a posttest may influence the results)

87
Q

Hawthorne effect

A

presence of the investigator affects participant responses
AKA reactivity
Hawthorn factory - production went up just because they knew they were being watched

88
Q

threats to internal validity of a study

A

history
selection (lack of random assignment)
statistical regression
practice effects (memory effects) on multiple testing situations
instrumentation (changes in instrument - paper and pencil vs computer)
attrition
maturation (any changes in the participant over time can affect the DV)
diffusion of treatment (effects of an intervention in one group are felt by another - kids talk about sex ed to another group)
experimenter affect (Hawthorne)
subject effects (pick up demand characteristics from the researcher or setting that motivate them in certain ways)

89
Q

demand characteristics

A

cues that research participants may pick up on from the researcher or research setting that motivate them in certain ways
messes with internal validity of a study

90
Q

stratified random sampling vs. cluster

A

stratified random - population is divided into subgroups, you choose randomly from the subgroups (quota sampling is this but without random selection of the participants from within the subgroups)
cluster - counselor identifies existing subgroups and not individual participants - least representative sample compared to other types of sampling

91
Q

multi-stage sampling

A

ID a. cluster then choose from within
e.g. randomly select 60 schools, then randomly select 10 classes from within
common in cluster sampling to provide better selection controls

92
Q

Common Rule

A

45 CFR 46

research that uses human subjects must have their studies approved by an IRB (if receiving federal funding)

93
Q

N

A

number of people being studied

94
Q

when a single-subject research design (SSRD) is with just one person, it may be called

A

idographic study
single case investigation
case study

95
Q

participant-observer model

A

researcher participates in the study while making observations about what transpired

96
Q

ABA research model

A

ABA: A = measure baseline; B = intervention is implemented; A = outcome is examined via a new baseline

97
Q

multiple-baseline design

A

when a researcher employs more than one target behavior

98
Q

an ABAB design is utilized to…

A

better rule out extraneous variables

99
Q

If removal of a treatment variable could be harmful to a subject, you should use a __ design

A

AB

100
Q

Pearson r

A

correlation coefficient

used for interval or Ratio (Pearson ‘R’) data

101
Q

___% of scores are within 1 SD of the mean
___% of scores are within 2 SD
___% of scores are within 3 SD

A

68%
95%
99.7%

102
Q

The larger the ____, the greater dispersion or spread of scores from the mean

A

range

103
Q

when a distribution has a lot of extreme scores (skewed), use the X rather than the X.

A

use the median rather than the mean

104
Q

factorial designs include 2+ ___

A

IVs

because several experimental values are investigated and interactions can be noted

105
Q

Solomon four-group design

A

helps you determine if your results are influenced by pretesting
two control groups, only one experimental group and one control group are pretested. the other groups are just post-tested

106
Q

y-axis AKA

A

ordinate

scale for the dependent variable

107
Q

x-axis AKA

A

abscissa

scale for the independent variable?

108
Q

inclusive range

A

highest score - lowest score + 1

regular range - no +1

109
Q

John Henry Effect

A

happens when participants strive to prove that an experimental treatment that could harm their livelihood isn’t that effective
AKA compensatory rivalry of a comparison group
threat to internal validity

110
Q

compensatory equalization

A

when the control group lowers their performance because they have been denied the experimental treatment
AKA resentful demoralization of the comparison group
threat to internal validity

111
Q

the range increases with ____

A

sample size

112
Q

z-scores are also called ____

A

standard scores, because they are the same as standard deviations

113
Q

ETS or CEEB score

A 
Educational Testing Service
or College Entrance Examination Board
scores range from 200-800
mean = 500
SD = 100
114
Q

you can __ and __ using interval scales, but you cannot __ or __

A

you can add and subtract

but not multiply and divide

115
Q

IQ tests are a kind of ____ measurement

A

interval (no true 0; a score of 0 does not mean 0 intelligence)

116
Q

Rosenthal effect

A

AKA experimenter expectancy effect
experimenter’s beliefs about a person may cause them to treat that person in a special way so that they confirm expectations
(e.g., teachers and favorite students)

117
Q

what ANCOVA really does

A

tests the means of 2+ groups after the random samples are adjusted to eliminate average differences
can be referred to as an “adjusted averages” procedure

118
Q

interquartile range

A

score distance between the 25th percentile and the 75th percentile

75th percentile - 25th percentile

119
Q

longitudinal research might also be called

A

diachronic method

as opposed to synchronic method (w/ cross-sectional design)

120
Q

non-directional experimental hypothesis
vs
directional experimental hypothesis

A

two-tailed t-test (IQ is different in the other group)

one-tailed t-test (IQ is higher in the other group)

121
Q

if an ANOVA yields a significant F value, name 3 tests you can use to determine significant differences between group means

A

Duncan’s multiple-range
Tukey’s test
Scheffe’s test

122
Q

multiple treatment interference

A

when a subject gets more than one treatment and you can’t tell which modality caused the change

123
Q

counterbalancing

A

switching the order in which stimuli are presented to a subject ina study; used to control for the fact that order can affect outcome

124
Q

Pygmalion effect

A

experimenter falls in love with their own hypothesis and the experiment becomes a self-fulfilling prophecy
AKA Rosenthal / experimentor effect

125
Q

quota sampling

A

population is divided into subgroups, you choose from the subgroups (stratified random but without random selection of the participants from within the subgroups)
non-probability sampling

126
Q

horizontal sampling

A

researcher selects subjects from a single SES group

127
Q

vertical sampling

A

people from 2+ SES groups are utilized

128
Q

systematic sampling

A

selection of every nth (i.e., 5th) subject

129
Q

probability vs non-probability sampling

A

probability - everyone has an equal chance of being included (random selection)
non-probability - samples of convenience

CPCE (9 decks)

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