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SLP PRAXIS > Research and Statistics > Flashcards

Research and Statistics Flashcards

1
Q

dependent variable

A

What is measured. It is what is affected by manipulation of the independent variable

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2
Q

Independent variable

A

The treatment measure - what is manipulated by the experimenter.

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3
Q

Cause-effect relationships

A

Can be found by experiments

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4
Q

Cross-sectional research

A

measures people from various age groups simultaneously

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5
Q

Ex Post Facto studies

A

(Retrospective / causal-comparative studies)
The independent variable (I e., # siblings, SES; # cigarettes) known. Start with effect and seek causes; no random assignment

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6
Q

Solomon Four-Group Design

A

With two control groups and two experimental groups. Half the groups have a pretest and half do not have a pretest. This tests both the effect itself and the effect of the pretest.

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7
Q

Between Subjects Design

A

Grouping Participants to Different Conditions

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8
Q

Within Subject Design

A

Participants Take Part in the Different Conditions - Also: Repeated Measures Design

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9
Q

Counterbalanced Measures Design

A

Testing the effect of the order of treatments when no control group is available/ethical

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10
Q

Matched subjects design

A

Matching participants to create similar experimental- and control-groups

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11
Q

Double-Blind Experiment

A

Neither the researcher, nor the participants, know which is the control group. The results can be affected if the researcher or participants know this.

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12
Q

Bayesian Probability

A

Using bayesian probability to interact with participants is a more dvanced experimental design. It can be used for settings were there are many variables which are hard to isolate. The researcher starts with a set of initial beliefs, and tries to adjust them to how participants have responded

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13
Q

Nominal Variables

A

Category or name

i.e. Girls / Boys

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14
Q

Ordinal Variables

A

Rank or ordering of levels

- Likert Scale

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15
Q

Interval Variables

A

Numerical with equal intervals or distance between numbers

- Scores on an exam

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16
Q

Ratio Variables

A

Same as interval scale but there is an absolute zero indicating an absence of the property measured
- i.e. Syllables stuttered

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17
Q

Single-Subject Designs

A
  • Help establish efficacy of treatment procedures and cause-effect relations
  • Dependent variables are measured continuously and results don’t require statistical analysis
  • Types include AB, ABA, ABAB, and multiple-baseline design
    A= skills measured without treatment or when withdrawn
    B= skills taught and results measured
18
Q

Multiple-Baseline Designs

A
  • A multiple baseline design can be across subjects so it includes several subjects who are taught one or more behaviors in a staggered way to show that only the behaviors of treated participants change.
  • A multiple baseline design can also be across settings
    • Collect base rates in 3 or more settings, teach behavior in one setting, repeat assessing in untreated settings then teach behavior in another setting. Teach in different settings until behavior is trained in all settings.
19
Q

Group Designs

A
  • Experimental or nonexperimental
  • True experimental research helps rule out effects of confounding variables by using randomization and a control group
  • Within subjects designs have one group
  • Between subjects designs have two+ groups
  • Pretest-Posttest Control Group Design
20
Q

Validity in Research

A

Degree to which an instrument measures what it intends to measure

  • Content validity
  • Criterion-related validity
    • Concurrent validity
    • Predictive validity
  • Construct validity
21
Q

8 Internal Validity Issues

A

Internally valid findings must reflect true cause-effect

  1. Instrumentation – measurement devices
  2. History – life events responsible for changes
  3. Statistical regression – behavior that is at poles (high or low) moves toward mean
  4. Maturation – unexpected biological changes in participants
  5. Attrition – mortality and drop-out rate
  6. Testing – repeated measurement
  7. Subject selection bias – factors influencing initial selection
  8. Interaction of factors – combination of above
22
Q

3 External Validity Issues

A

Externally valid findings must have generalizability

  • Hawthorne Effect – study’s results affected by fact that people know they are taking part in an experiment
  • Multiple-Treatment Interference – can be a concern when 2+ treatments are administered to the same person; order effects can also be a concern
  • Reactive or Interactive Effects of Pretesting – may be a problem if the pretest measure is also the dependent variable
    • for example, a vocal hygiene questionnaire is given to a control group subject who then tries to modify his vocal abuse
23
Q

Reliability in Research

A

Consistency with which something is measured on repeated occasions

  • Test-retest reliability
  • Alternate-form reliability
  • Split-half reliability
  • Interobserver / interjudge reliability
  • Intraobserver or intrajudge reliability
24
Q

Inductive method

A

Specific to general

  • Conclusion based on patterns that you see.
  • Experiment first and draw conclusion next.

EXAMPLE: What is the next number in the sequence 6, 13, 20, 27

25
Q

Deductive method

A

General to specific

  • Conclusion based on previously known facts.
  • Make a conclusion first and verify later.

EXAMPLE: All men are mortal. (major premise)
Socrates is a man. (minor premise)
Therefore, Socrates is mortal. (conclusion)

26
Q

Levels of Evidence

A

Ia
Well-designed meta-analysis of >1 randomized controlled trial (using a systematic review)
Ib
Well-designed randomized controlled study
IIa
Well-designed controlled study without randomization
IIb
Well-designed quasi-experimental study including a cohort study or case-controlled study from independent researchers
III
Well-designed non-experimental studies, i.e., correlational and case studies including time-series single-subject investigations
IV
Expert committee reports, opinions of authorities, descriptive studies, and descriptive clinical cases

27
Q

Probability

A

Alpha level of p <.05

28
Q

Effect Size

A

Cohen’s d of .3 for small, .5 for medium, and .8 for large

29
Q

Variability - dispersion or spread in data set

A

Standard deviation

30
Q

Central Tendency – distribution of set of scores reflecting the average

A

Mean, median, mode

31
Q

Parametric Statistics (vs non-parametric)

A

Paremetric statistics require that assumptions be met about distributions:

  1. Adequate sample size
  2. Homogeneity of variance
  3. Fairly normal distribution

Parametric statistics are more powerful but sensitive to violations of the assumptions

Parametric = t-test (no more than two groups)
- or ANalysis Of VAriance (ANOVA) with two or more groups (Example - boys and girls at different ages on vocabulary)

32
Q

Non-Parametric Statistics (vs parametric)

A

Non-parametric tests do not make an assumption about the data, they require less information.

They are less powerful than the parametric tests and it tends to be more difficult to find statistical significance.

Standard parametric tests also have corresponding non-parametric counterparts.

  • Wilcoxon Signed Rank test / Paired t-test
  • Kruskal-Wallis test / One-way between-subjects ANOVA
33
Q

Positive predictive value

A

95% probability that child who fails screener will be identified by formal testing as having a speech problem

34
Q

Negative predictive value

A

95% probability that a child who passes the screener will be identified as having normal speech

35
Q

Sensitivity

A

Percentage of true positive results

36
Q

Face validity

A

Extent to which measure looks valid to the examinee

37
Q

Content validity

A

The extent to which a measure represents all facets of a given social construct.

38
Q

Reliability coefficient

A

High reliability coefficient=test yields replicable results

39
Q

Standard error of measurement

A

Low=test yields precise or accurate results

40
Q

Criterion Validity

A

a measure of how well one variable or set of variables predicts an outcome based on information from other variables, and will be achieved if a set of measures from a personality test relate to a behavioral criterion on which psychologists agree

  1. Concurrent validity- demonstrated where a test correlates well with a measure that has previously been validated. The two measures may be for the same construct, or for different, but presumably related, constructs.
  2. Predictive validity - the extent to which a score on a scale or test predicts scores on some criterion measure
41
Q

Construct validity

A

Refers to whether a scale measures or correlates with the theorized psychological scientific construct (e.g., “fluid intelligence”) that it purports to measure. In other words, it is the extent to which what was to be measured was actually measured.

42
Q

The effectiveness of tx can be best demonstrated by

A

Single-subject design

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