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PYB210 > Week Four > Flashcards

Week Four Flashcards

1
Q

internal validity

A

how sound is the design, how strongly can we assert that changes in our DV are down to our IV and not other things we haven’t controlled for.

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2
Q

external validity

A

how generalizable are our findings, how representative of the real world is the study.

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3
Q

steps to internal validity

A
  • Sound operationalisation of the DV
    ○ Measures should be reliable and valid.
    • Strong experimental design logic
    • Sound operationalisation of our Ivs
    • Consideration and use of appropriate remedies to control for extraneous variables.
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4
Q

factorial

A

more than one IV
○ May have all repeated measures or all between groups or mixed.
○ Allows examination of interplay between two or ore Ivs and the splitting p of these effects into interactions and main effects.

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5
Q

strengths of factorial designs

A

○ More than one independent variable allows for more precise hypotheses.
○ Control of extraneous variable by including as an independent variable.
Ability to determine the interactive effect of two or more independent variables

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6
Q

main effect

A

○ The influence of one independent variable on the dependent variable
One main effect for each IV in a study

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7
Q

interaction effect

A

○ The joint, combines or interactive effect of two or more independent variables on the dependent variable.

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8
Q

factorial design notation

A

2 x 3

= 2 IVs, one 2 levels and one 3 levels

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9
Q

weakness of factorial design

A
  • Using more than 2 IVs may be logistically cumbersome.

- Higher order interactions are difficult to interpret.

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10
Q

variability

A

In any study, what we are trying to do is establish whether the variation in the DV between groups I different from the normal variation in the DV within groups.

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11
Q

how to ensure a strong experimental design

A
  • In order to maximise our chances of getting a true picture of how the IV affects the DV we need to:
    ○ Maximise the impact on our dependent variable that is related to the independent variable.
    § Increase between group/condition/level variation.
    ○ Minimise variation in our dependent variable that is not related to our independent variable
    § Compress within group/condition variation.
    Done by adopting good research design and controlling variables.
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12
Q

separation

A

In any experiment we are trying to establish whether the variation in the DV between groups (caused by the IV) is different from normal variation in the DV within groups.

Separation of the IV and DV: achieved by IV operationalisation

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13
Q

compressions

A

achieved by controlling extraneous variables.

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14
Q

types of extraneous variables

A

○ Noise creating
§ Randomly impact the DV, not related to the IV, but potentially create extra variation in the DV not due to the IV, want to minimise this.
§ Has an effect randomly on the DV
○ Confounding
§ Systematically impact the DV, related to the IV, potentially explaining changes in the DV that you would be expecting the IV to make, want to control for this by eliminating, keeping constant or building into study so can measure impact.
§ Varies systematically on the DV.

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15
Q

EVs and between groups

A
  • Two separate groups of people who could differ on a whole range of things. Both relevant and irrelevant to the study at hand.
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16
Q

self assignment

A

Self assignment: subject selects which treatment groups

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17
Q

experimenter assignment

A

experimenter selects which treatment group.

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18
Q

arbitrary assignment

A

selection based on seemingly non-relevant criteria.

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19
Q

random assignment

A
  • Random Assignment/Allocation: best to have no criteria for selection.
    ○ Provides max. insurance that the groups are equal.
    ○ Eliminates systematic differences between groups.
    ○ Doesn’t eliminate Evs but does help to decrease.
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20
Q

matching

A

○ Use of a variety of techniques to equate participants in the treatment groups on specific variables.
§ Should be done with variables thought to be related to the IV or may confound the IV
□ E.g. intelligence, age etc.
○ Advantages
§ Controls for the variables on which participants are matched
§ Increases the sensitivity of the experiment.

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21
Q

individual matching

A

○ Advantage
§ Groups equated on potential EV.
○ Disadvantages
§ Identifying the variables on which to match.
§ Difficulty matching participants increases as the number of variables on which to match increases.
§ Decrease in generalisability of results.

22
Q

distribution matching

A

Run a algorithm to ensure each group is equal.

23
Q

to eliminate EVs

A
  • To eliminate EVs, built it into the design (blocking).
    ○ Make the EV another IV in the design
    ○ Should only be used when you are interested in the effect of the extraneous variable.
24
Q

problems with repeated measures deigns

A
  • order effects
  • practice effects
  • fatigue effects
25
Q

order effects

A

○ When participants are exposed to Ivs in a particular order

26
Q

practice effects

A

Differences or improvements may occur simply due to practice rather than the IV.

27
Q

fatigue effects

A

Participant is bored and pays less attention.

28
Q

control for effects

A
  • counterbalancing
  • randomised counterbalancing
  • intra-subject counterbalancing
  • complete counterbalancing
  • incomplete counterbalancing
29
Q

counterbalancing

A

○ Breaking our sample into subsets and presenting the conditions in different orders.
○ By collapsing this data again it will hopefully counteract any sequencing effects.

30
Q

randomised counterbalancing

A

Participants are randomly exposed to levels of the IV in a random sequence.

31
Q

intra-subject counterbalancing

A

○ Participants take treatments in more than one order

32
Q

complete counterbalancing

A

Every participant is exposed to every possible sequence of the IV.

33
Q

incomplete counterbalancing

A

most commonly used.

34
Q

simple carry over effects

A

○ Where performance on the DV in one condition is contaminated by the effects of the previous condition

35
Q

differential carry over effects

A

○ Unique to one condition only.

○ Is different depending on the order in which the participants are exposed.

36
Q

time as an IV

A 
- 	- Occurs if you measure people at different times
Can cause design effects 
- maturation
- external effects 
- statistical regression 
- mortality
37
Q

maturation

A

changes due to the natural development, natural expected improvement over time.
§ Is it because of the IV or just because people are getting better at it over time.

38
Q

external effects

A

§ External events that affect participants during the study.
§ Socio-historical-economic changes relevant to outcome.
□ i.e hearing about a shooting can impact your view on gun laws.

39
Q

statistical regression

A

§ Refers to the tendency to move up or down towards the mean over time
People are likely to move towards the mean eventually.

40
Q

mortality

A

§ Attrition from the study (leaving the study): not all participants will remain in the study until the end.
§ Common in longitudinal studies
Do the people who remain in the study differ systematically to those who drop out?

41
Q

experimenter effects

A
  • measurement issues
  • attribute effects
  • experimenter expectancies
42
Q

measurement issues

A

problems with equipment or errors.

§ To control this: training, careful measurement, attention to detail.

43
Q

attribute effects

A

participants responding differently depending on the experimenter.
§ Control: randomise the experimenter or use the same experimenter for the entire time.

44
Q

experimenter expectancies

A

likely response of participants and its manipulations may lead to subtle differences in the way the experimenter interacts with participants which leads to differences in outcomes.
§ Rosenthal effect: differential attitude or attention conveyed to participant expected to respond most favourably to the study.
§ Golem effect: differential attitude or attention conveyed to participant expected to respond least favourably to the study.

45
Q

controls for experimenter effects

A

§ Double blind: neither the experimenter or the participant is aware of the treatment condition administered to the participant.
□ i.e. a drug and a placebo where the experimenter and the participant doesn’t know what they were given.
§ Partial blind
□ Knowledge of each participants treatment condition is kept from the experimenter through as many stages of the experiment as possible
§ Automation
□ No contact
□ i.e. experiment done via a computer.

46
Q

participant effects

A
  • demand characteristics
  • social desirability
  • hawthorne effect
47
Q

demand characteristics

A

participant gets inkling about what study is aiming for an performs in a way to conform to those expectations.

48
Q

social desirability

A

participant performs in a way they thin will be most pleasing to experimenter or will paint them in the best light.

49
Q

hawthorne effect

A

participant improves or changes performance on the outcome purely as a function of the attention received for the study and not as a function of the nature of the manipulations of the IV.

50
Q

situational effects

A

○ The impact of environmental and timing difference on participants’ outcome scores. Can include time of day, weather, lighting, etc.
○ Can be controlled by keeping these constant for all participants.

51
Q

control groups

A

○ Allows you to directly examine the extent to which changes would have occurred without your intervention.
○ Make sure you endeavour to have an ‘equivalent’ control group.
○ May have multiple control groups
§ No intervention
§ Placebo intervention

PYB210 (10 decks)

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