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CPCE > Research > Flashcards

Research Flashcards

1
Q

What is research?

A

The systemic process of collecting and analyzing data

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2
Q

What is evidence based inquiry?

A

Search for knowledge using empirical data which has been gathered systematically.

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3
Q

What is inductive research?

A

Begins at the real world, practical level. Descriptive, correlational, or historical and leads to the building of theory.

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4
Q

What is deductive research?

A
  1. Springs from theory that is already established.
  2. Tries to determine what the relationships are between elements of the theory
  3. May be experimental in nature
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5
Q

Survey

A
  1. Non experimental
  2. Measures attitudes and perceptions
  3. Not easily generalizable unless subject pool is representative
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6
Q

Descriptive research

A
  1. Non experimental
  2. Describes an existing state of events
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7
Q

Comparative research

A
  1. Non experimental
  2. Investigates if there are differences between one or more groups
  3. No manipulation of conditions
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8
Q

Correlational research

A
  1. Non-experimental
  2. Uses the correlation coefficient to determine the degree of relationship between two or more variables or phenomena.
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9
Q

Ex post facto research

A
  1. Non- experimental
  2. This research design studies possible causal relationships among variables ex post facto (after the fact).
  3. No manipulation of variables
  4. Generate several reasons (causes) for the relationship
  5. Statistics used are t-test and analysis of variance
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10
Q

True experiment

A
  1. Experimental and control groups with random assignment
  2. Determine cause-and-effect relationships
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11
Q

3 types of experiments

A
  1. Treatment and control group with post test only
  2. Treatment and control group with pretest and post test
  3. Two different treatment groups with control group and post test
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12
Q

Quasi experiment

A
  1. Similar to experimental research except that randomization of subjects to treatment and control groups is not possible.
  2. Example two classrooms of 4th graders
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13
Q

Qualitative research

A

Emphasizes gathering data about naturally occurring phenomena (individuals and groups living experiences) and events.

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14
Q

Two types of interactive qualitative research designs

A
  1. Case study: in depth examination of a particular case
  2. Ethnography: description and interpretation of cultural or social group or system
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15
Q

Non interactive qualitative research design

A
  1. Analytical research conducted primarily through document analysis.
  2. Examples: historical analysis, biographical analysis (written or oral), legal analyses (law and court decisions).
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16
Q

Mixed method research design

A
  1. Combine quantitative and qualitative in the same research effort
  2. Typically used sequentially
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17
Q

Single-subject design

A

Studies the effects of a program or treatment on an individual or group treated as an individual usually after a baseline has been established

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18
Q

Action research

A

Attempt to improve services or a program. Usually has an evaluative function.

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19
Q

Pilot study

A

A small scale research effort often used to detriment the feasibility of large scale effort.

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20
Q

Longitudinal research

A

Collecting data from the same forks of individuals over a period of time also called a panel study.

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21
Q

Cross sectional research

A

Collecting data from different groups at the same time and examining the differences.

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22
Q

Examining what changes occur within the members of a group

A

Within-subjects

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23
Q

Examining what changes occur between two or more groups

A

Between subjects

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24
Q

Meta-analysis

A

Research comparing findings across studies

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25
Q

Internal validity

A

Extraneous variables have been controlled

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26
Q

Confounding variables to internal validity

A
  1. Selection of subjects (not randomly selected
  2. Instrumentation
  3. Maturation (changes do to maturation not treatment)
  4. Mortality or attrition (losing subjects )
  5. Experimenter bias
  6. History or extraneous incidents
  7. Statistical regression (subjects are recruited because of extreme high or low scores
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27
Q

External validity

A

Results are generalizable

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28
Q

Threats to external validity

A
  1. Selection of subjects
  2. Ecological validity (generalizable form one setting or circumstance to another)
  3. Reactivity
  4. Novelty and disruption (being selected energizing or exciting swaying response)
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29
Q

4 types of reactivity

A
  1. Hawthorne effect - subject knows they are being watched
  2. Demand characteristics- what subject has been told or knowledge they have acquired influencing performance
  3. Experimenter bias, rosenthal, pygmalion
  4. Placebo
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30
Q

4 Levels of measurement

A
  1. Nominal
  2. Ordinal
  3. Interval
  4. Ratio
31
Q

Nominal measurement

A
  1. Numbers represent qualities or categories (male and female)
  2. Use a non parametric statistic such as chi-square
32
Q

Ordinal measurement

A
  1. Represents differences in magnitudes of the variable
    2.data that can be ranked
33
Q

Interval measurement

A
  1. The intervals between the numbers on a scale contain the same amount of the variable.
  2. Example: on a Standardized test the distance (interval) between 11 and 12 is the same as the distance between 24 and 25.
  3. Example Fahrenheit
34
Q

Ratio measurement

A
  1. Numbers are on a scale which has a true zero.
  2. Numbers can be compared by ratios
  3. You cannot say someone is twice as introverted as someone else because there is no base
  4. Weight has a true zero for example because you cannot be negative pounds
35
Q

Sampling

A

Selection of a part of the population

36
Q

Random sampling

A

Equal and independent chance of being selected

37
Q

Stratified sampling

A

Major subgroups in the population will be sampled (ethnicity, gender, race)

38
Q

Proportional stratified sampling

A

Randomly selecting the same proportion of individuals in subgroups which is representative of population.
Example: one half of population is Hispanic one half is white sample would mirror these proportions

39
Q

Cluster sampling

A

Naturally occurring groups of individuals such as classrooms or City blocks. Clusters randomly selected.

40
Q

Sample size

A

Size influences statistical hypothesis testing.
Suggested minimum sample sizes
Correlational: 30
Ex post facto and experiment: 15
Survey: 100

41
Q

4 types of statistic analysis

A
  1. Descriptive - describe data collected (summary)
  2. Inferential - make inferences from sample to population
  3. Parametric - data normally distributed
  4. Non parametric - cannot be normally distributed (chi squared)
42
Q

Independent variable

A

Variable you manipulate

43
Q

Dependent variable

A

Variable you are measuring or trying to change. Depends upon the value of the independent variable.

44
Q

Null hypothesis

A

No difference between the variables or groups measured

45
Q

Alternative hypothesis (directional)

A

One groups scores will be significantly different (one tailed test)

46
Q

Alternative hypothesis (nondirectional)

A

There will be differences between the groups but which group had higher or lower scores is not indicated (two-tailed test)

47
Q

Significance level

A

Significant level you select will determine the likelihood or making an error in accepting or rejecting the null

48
Q

Type I or Alpha error

A

Rejection of null when it is correct

False positive

49
Q

Type II error (beta)

A

Failure to reject the null hypothesis when there is in fact a difference

False negative

50
Q

As significance level goes down ( .05 to .01) type 1 error decreases and type two error increases

A

Alpha (Type I) error: Reject (null hypothesis) when shouldn’t.

Beta (Type II) error: Retain (null hypothesis) when shouldn’t.

51
Q

T-test

A

Used to determine whether the mean scores of TWO groups are significantly different from each other.

52
Q

One-way Analysis of Variance

A

One variable and different levels (therapists at LPC, LSW, PHD) uses F values and F distribution.

53
Q

Factorial analysis of variance (ANOVA)

A

Factorial (ANOVA): simultaneously determine whether mean scores in two or more variables (factors) differ significantly.

1 dependent variable (self esteem)
2 or more independent variables (gender and therapist level)

54
Q

Multivariate analysis of variance (MANOVA)

A

More than one dependent variable
You must use MANOVA instead of ANOVA

55
Q

Analysis of Covariance (ANCOVA)

A

Similar to analysis of variance except that the Influence of one or more independent variables on the dependent variable is controlled.

56
Q

What test do you apply if an ANOVA test yields a significant F value to determine whether a particular group mean or combination of group means are significantly different?

A

Post hot or multiple comparison tests

57
Q

Scheffe’s, Tukey’s HSD, Newman-Keuls, Duncan’s new multiple range test are all examples of what kind of tests?

A

Post hoc and multiple comparison tests

58
Q

When do you use a non parametric test?

A

If a distribution of scores is not normally distributed or the variance of your sample is similar to the variance of the population (homogeneity).

59
Q

Mann-Whitney U test

A

Nonparametric test

When you collect data from two samples that are independent from each other and the scores are not normally distributed.

60
Q

Wilcoxen signed-rank test

A

Scores from two samples and these scores are correlated but they do not approximate a normal distribution.

61
Q

Kruskal-Wallis test

A

Non parametric test
When you have more than two mean scores on a single variable. This is a nonparametric one-way analysis of variance.

62
Q

Chi squared

A

Nonparametric test
Used when you have nominal data (groups or categories)
Used to determine whether two distributions differ significantly

63
Q

Solomon four-group design

A

Examines the effect of any pretest used on the experimental treatment.

64
Q

Multiple regression

A

Use of the correlation coefficient to determine the strength of the relationship of predictor (independent) variable on a criterion (dependent variable.

Adds together the predictive powe of several independent predictors (independent variables)

examples of predictors variables GPA, class rank, ACT

65
Q

Scatterplot

A

Graphic representations of the relationship between two variables for a group of individuals.

Reference photo

66
Q

Factor analysis

A

Use of correlation coefficient to determine whether a set of variables can be reduced to a smaller number of factors.

Example: a factor analysis of a long inventory with 15 scales may uncover only 4 or 5 factors that are independent of one another because parts of the scales overlap

67
Q

Likert scale

A

Measures attitudes and opinions
(Agree, strong agree, disagree, strongly agree)

68
Q

Cross- sectional study

A

Studying or measuring characteristics of several groups at the same time

69
Q

Longitudinal study

A

Studying or measuring characteristics of a group over time

70
Q

Double blind

A

When neither researcher nor the subject knows who is receiving the active substance or the placebo

71
Q

Halo effect

A

Tendency for the observer to form an early impression of the person being observed and that creating a bias.
Can be positive or negative

72
Q

Formative evaluation

A

Determine how well a new technique, process or, treatment works.

“Process evaluation”

73
Q

Summative evaluation

A

Summary or product evaluation used to measure how well an agency or program has met their goals.

“Product evaluation”

CPCE (9 decks)

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