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PSYO 2000 > Measuring Behaviour Etc > Flashcards

Measuring Behaviour Etc Flashcards

1
Q

Operational definition

A
  • the phenomena to be measured should be defined in terms of the operations used to measure them
  • a good operational definition is reliable and reproducible
  • loss of contract validity can occur (conventional meaning may be lost)
  • eg: alcoholism, PMS, ADHD etc
  • essential in experimental research
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2
Q

Ostensively definitions

A

-phenomena to be observed should be carefully described (textually, graphically, photographically) and examples can be given
-common in observational research
(Basis of ethograms and systematic behaviour)

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3
Q

Nominal scales

A
  • categories, taxonomies, typologies
  • eg: male/female; liberal/conservative/democrat; ADD+H/ADD-H; extroverted/introverted
  • types of statements: x is different from y; assignment of labels
  • purely qualitative information
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4
Q

Ordinal scales

A
  • continuum or spectrum of observations.
  • ranking within a category is possible; often different names and certainly different quantities
  • absolute values not known
  • eg: low, moderate, high self-esteem; ranking of a race
  • types of statements: x is greater than y; assignment of values
  • qualitative with some crude degree of quantity (ranked)
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5
Q

Interval scales

A
  • has no absolute zero point, i.e. arbitrary
  • eg: Celsius scale (0 is a relative point on the scale, when ice melts; it is a convenient convention). Likert scales
  • common in psychology and neuro: rating scales, from 0-10 (where 0 does not mean no liking at all), IQ scale (0 does not mean no intelligence)
  • quantitative; we know by how much the values differ
  • spacing between values is known, but a score 120 is not necessarily double a score of 60
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6
Q

Ratio scales

A
  • has an absolute zero point (absence of the quantity can be indicated)
  • zero means zero
  • eg: Kelvin (0K is the absence of heat
  • common in psych and neuro: from no response to n degree of response
  • eg: score on memory test
  • quantitative; we know how much of the quantity exists
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7
Q

Scales of measurement: the implications

A
  • nominal and ordinal can be analyzed with a number of non-parametric statistical analyses
  • interval and ration analyzed with parametric stats
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8
Q

Environmental/situational variables

A
  • variables referring to the manipulation of the environment
  • eg: treatment, tasks
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9
Q

Instructional variable

A
  • variables referring to what is told to a participant, instructed, or simply suggested
  • applies mostly to human research and animal research
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10
Q

Subject, participant, or individual variables

A
  • quasi independent variables
  • differences in individuals
  • eg: ethnicity, habits, diseases etc
  • important in idiographic vs nomothetic research
  • not true independent variable because it is not manipulated
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11
Q

Controlled variables

A

-any variable that is controlled or held constant across all treatment conditions of experiment

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12
Q

Extraneous variables

A
  • “threatening variable”
  • “obscuring factors”
  • impact on dependent variable that is not ind variable
  • variables that are not being studied
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13
Q

Confounding variables

A
  • an extraneous variable (usually unmonitored) that can inadvertently affect another experimental variable
  • potential source of variability (experimenter-expectancy effects
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14
Q

Solutions for confounding/extraneous variables

A
  • random assignment of participants to treatment conditions
  • keeping extraneous variable constant
  • matching participants on extraneous variable
  • building the extraneous variable into study or blocking so that the extraneous variable becomes an independent variable
  • statistical control of variable: ANCOVA so that extraneous variable become a covariate
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15
Q

Experimental research designs and variables

A

goal: causal relationships

Variables: IV=manipulated by experimenter; DV=measured by experimenter

Issues: internal validity (confounding variables); external validity: generalizability, ecological validity.

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16
Q

Correlational research designs and their variables

A

Goal: correlational relationships

Variables: predictor=used to make a prediction; criterion=predicted variables

Issues: directionality problems A->B, B->A, AB?
Third variable problem: not AxB, but AxC

17
Q

Threats to interference

A
  • experimenter-expectancy effects; confirmation bias
  • demand characteristics: subjects own expectancies; can occur in animals also
  • subject predisposition effects
    • cooperative-subject: want to provide data that will support hypothesis
    • screw you effect: want to sabotage experiment
    • evaluation apprehension: want positive evaluation; hypothesis independent
    • faithful subjects: do what they are asked
  • placebo effect
18
Q

Control groups

A
  • control groups: do not get the independent variable (manipulation, treatment, etc)
    • placebo: control group that receives dummer treatment (sugar pill) that is assumed to have a positive effect
    • nocebo: opposite of placebo… effect of IV is worse not better
    • sham group: surgery with no experimental purpose
  • quasi control: subjects in this group dont get placebo
    • sub type: simulator groups - subjects are asked to act as if they had received treatment. Useful in double-blind experiment to detect and assess experimenter-expectancy effects and demand characteristics
19
Q

Single-blind procedure

A

Minimized demand characteristics; not always possible because of informed consent requirements

20
Q

Double-blind procedure

A

-reduce demand characteristics and experimenter-expectancy effects

21
Q

Partial-blind procedures

A
  • experimenter not in the know until just before the treatment is about to be administered
  • can minimize experimenter-expectancy effects
22
Q

Debriefing

A

-asking subjects about what they think happened to identify problems with demand characteristics

23
Q

Basic techniques for experimental control

A
  • single blind
  • double blind
  • partial-blind
  • deception
  • disguised-experiment technique/unobtrusive experimentation
  • debriefing
24
Q

Multiple researchers control

A
  • having multiple experimenters, observers, handlers, trainers etc
  • useful if you suspect experimenter effects
25
Q

Experimenter-expectancy control groups

A
  • 3 groups of researchers formed
  • group 1: led to expect one experimental outcome
  • group 2: led to expect opposite experimental outcome
  • group 3: led to expect no effect
26
Q

Unrelated-experiment technique control

A
  • separate the presentation of the IV over the DV. TWo experiments are necessary (within design so subjects do both)
  • experiment 1: subjects receive IV
  • experiment 2: subjects receive DV
  • subjects are told the two experiments are not connected
27
Q

Experiment with all control groups

A

1: receive 1 mg of melatonin
2: receive 3 mg of melatonin
3: control - placebo (sugar pill)
4: quasi control: no placebo

28
Q

Random sampling

A
  • single random sampling
  • Stratified random: random sampling within segments (strata) of the population based on specific characteristics are considered (age, gender etc)
  • cluster sampling: naturally occurring units of individuals (groups) are randomly selected. Eg. Children in day care group, students in this class.
    • proportionate sampling to avoid over representation
29
Q

Non-random or non-probabilistic sampling

A
  • haphazard sampling (not true random sampling)- example with grabbing fish from tank
  • convenience sampling
  • volunteer sampling
  • systematic sampling (every nth element sampled)
  • sequential sampling: gradual, one at a time
  • quota sampling: stratified without randomness (based on convenience sampling principles)
  • purposive/selective: selection based on pre-determined criterion
30
Q

Selective sampling, non-sampling, and strong criterion based sampling

A
  • sometimes look for exceptional individuals, highly qualified
  • eg: police dogs, traffic controllers, med students
31
Q

Random sampling

A

-selecting subjects from a population so all members have same chance of being selected for a sample (and all possible sampled have the same chance of being selected)

32
Q

Random assignment

A
  • using random chance to determine which condition a participant will experience
  • determines difference between experimental and quasi experimental research

PSYO 2000 (9 decks)

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