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research design Flashcards

1
Q

research design is the

A

overall plan for answering the research question

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2
Q

question should have

A
  1. nature of comparison
  2. type of setting
  3. population, sample
  4. independent and dependent variable
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3
Q

comparisons between two groups or more

A
  • single group: 2 or more points in time (pre/post)
  • single group under different circumstances or experiences (group vs individual therapy)
  • based on relative rankings (severe vs mild autism)
  • compare with samples from other studies
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4
Q

research designs also include

A
  • methods to be used to contol variables (isolate dependent and independent variables)
  • timing and frequency of data collection (when, relative to other events)
  • setting (naturalistic vs laboratory)
  • nature of communications with subjects (fully divulge or not)
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5
Q

dimensions along which designs can be described

A
  1. experimental vs non-experimental
  2. degree of structure imposed
  3. time dimension
  4. type of group comparisons between subjects and within subjects
  5. non-experimental
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6
Q

experimental

A

quantitative

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7
Q

non-experimental

A

qualitative

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8
Q

degree of structure imposed

A

how much we are controlling

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9
Q

time dimension

A
  • longitudinal

- cross-sectional

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10
Q

longitudinal

A

looking for change in time

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11
Q

cross-sectional

A

collecting data at 2 points in time

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12
Q

multiple points of data collection secondary to

A

studying time related processes
determine time sequences
developing comparisons
enhancing research control

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13
Q

trend studies

A

periods of time

observing what’s going on with trends

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14
Q

cohort

A

when you take a small population (by age)

study them over time with respect to a phenomenon (subject)

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15
Q

panel studies

A

take same cohort and measure across 2 periods of time

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16
Q

follow up studies

A

how they feel about same topic in a period of time

ex 5 years down the line

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17
Q

cross section cohort

A

comparing 2 different cohorts follow up study can be a panel study

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18
Q

within subjects

A

in same group of people (more control of variables)

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19
Q

between subjects

A

different group of people

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20
Q

non-experimental

A

not manipulating anything (qualitative)

  • retrospective
  • prospective
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21
Q

retrospective

A

have an outcome

want to know what causes are (antecedent) study prior habits

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22
Q

prospective

A

know causing variables
going forward in time
see how many develop outcomes

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23
Q

usually do prospective after you gain evidence from

A

retrospective

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24
Q

cons of retrospective

A

memory might not be accurate
might get defensive
might not tell the truth

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25
characteristics of a good design
- must be appropriate to question asked - minimize biases that can distort results of study - precision must be enhanced - power should be adequately dealt with
26
biases result from
1. differences among participants in groups 2. researchers preconceptions 3. use triangulation
27
differences among participants in groups
more so in non-random groups
28
researcher's preconceptions minimize this
can do a double blind study | neither participant nor data collector knows specific research objectives
29
use triangulation to
reduce bias | at least 3 points of data collection
30
precision must be enhanced
sensitivity with which effect of independent variable relative to effects of extraneous variable (confounding) can be detected want it high
31
power should be adequately dealt with
ability of design to create maximal contrast amongst group being compared one can detect relationship between variables
32
experimental designs
characteristics of true experience
33
characteristics of true experience
- manipulation - control - randomization
34
manipulation
independent varibale
35
control
not getting any treatment outside things that impact treatment ex control environment
36
randomization
``` pick random from different population extreme view will be cancelled equal chance that they can be picked for any group -table of random #s -cluster randomization -matching ```
37
table of random #'s
flipping a coin, most reliable method for equating groups on all possible characteristics that could effect outcome of study
38
cluster
picking people in clusters, random, pick a bunch to represent zip code
39
matching
people in each group match and have equal numbers
40
experimental designs
- basic - Solomon 4 group design - factorial design - repeated measures - randomized control trials
41
posttest only
someone's been given a treatment and measuring outcome after the fact
42
pretest
measuring outcomes before and after
43
basic
- posttest ony | - pretest/postest
44
Solomon 4 group design
take into account influence of pretesting on subsequent posttest results
45
factorial design
1 independent and 1 dependent - main effects - interaction effects
46
main effects
1 variable
47
interaction effects
combine independent varibales
48
quasi experimental designs
- manipulation + control or randomization - non-equivalent control group design - time series designs - times series: non-equivalent control group design
49
non-experimental designs 2 broad classes
1. ex-post factor research | 2. descriptive
50
ex-post factor research
coorelational
51
descriptive
- descriptive correlational - univariate descriptive - retrospective - prospective
52
other non-experimental types
- survey research - evaluation research - needs assessment - secondary analysis - meta analysis - historical research - case studies (single subject designs)
53
qualitative designs field studies
- ethnography - phenomenology - grounded theory
54
ethnography
roots in anthropology
55
phenomoneology
roots in philosophy
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ethnomethodology
roots in sociology
57
ethnomethodology
roots in sociology
58
strategies in a research study
- triangulation - mixed methods - fully integrated
59
integrated research designs 2 broad categories in multi-method research
- component | - integrated
60
component
- triangulated - complementarity - expansion
61
integrated
- iterative - embedded or nested - holistic - transformative
62
advantages of experimental designs
most powerful method available for testing hypotheses of cause and effect relationships between variable
63
disadvantages of experimental designs
many situations in which experimental design is impossible, secondary to ethical or protocol considerations, artificiality or setting, randomness not always real
64
Hawthorne effect (placebo effect)
knowledge of being included in a study may be sufficient to cause people to change their behavior
65
study could have double hawthorn effect
when those conducting study also change their behavior | therefore, do a double blind study so neither researcher nor subject know
66
repeated measures design
-one group tested under all conditions (within subjects design)
67
repeated measures design
-one group tested under all conditions (within subjects design)
68
one group tested under all conditions (within subjects design) strong design because of
ability to control potential influence of individual differences
69
one group tested under all conditions (within subjects design disadvantage is practice effects
exposure to test | one way to combat this is increase length of time between treatments, so subject's scores can go back to baseline
70
one way repeated measures design
one group of subjects exposed to all levels of one Independent variable order effects can occur, that is potential biasing effect of test sequence, so randomize order of presentation for each subject one way ANOVA test
71
crossover design
- only 2 levels of individual variable - half receive treatment A, then treatment B - half revieve treatment B followed by treatment A - again add time in between to remove any testing effect or treatment residual effect - 2 way ANOVA, paired t-test
72
two way design with two repeated measures
- 2 individual variable with two levels each - subjects get all 4 conditions - 2 way ANOVA
73
efficacy
examining benefit of treatment as compared to control group or standard of care group
74
effectiveness
benefits and use of procedures under real world conditions
75
quasi experimental designs
- manipulation + control OR randomization - non-equivalent control group design - time series designs
76
time series
non-equivalent control group design
77
quasi experimental designs: one group-pre-test/post-test design
paired t-test, on small samples with ordinal data-Wilcoxon sign rank
78
quasi experimental designs: one way repeated measures design
one way ANOVA
79
quasi experimental designs: time series design
- multiple measures before and after tx, to document trends | - use graphic visual analysis
80
quasi experimental designs: non-equivalent pre-test/post-test control group design
- groups are not equal | - paired t-test, ANOVA
81
quasi experimental designs: non-equivalent post-test only control group design
- regression analysis | - discriminant analysis
82
non-experimental designs: 2 broad classes
- ex-post facto research | - descriptive
83
non-experimental designs: ex-post facto research
- after fact (intervention) | - correlational
84
correlational
- degree of association among variables | - it is a function of covariation in data
85
non-experimental designs: descriptive
- descriprive correlational - univariate descriptive - retrospective - prospective
86
descriptive coorelational
describe nature of existing relationships
87
univariate descriptive
one variable
88
retrospective
examine data collected in past
89
prospective
current data and follow up in future
90
non-experimental designs (quantitative)
- survey research - evaluation research - needs assessment - secondary analysis - meta analysis - content analysis - historical research - case studies
91
survery research
statistical
92
evaluation research
- how well something is doing? (standardized) | - what is going on?
93
needs assessment
collect data on what place is like/what they need may have multiple needs
94
secondary analysis
take existing data set ask different research question and alalyze
95
meta analysis
take a bunch of study that are asking same question and their population combine statistically (quantitative)
96
content analaysis
- can be numerical/qualitative | - frequency of idea
97
historical research
go back and look at old records/artifacts to recreate history
98
cases studies
look at individual in depth every client factor look at them historically -single subject designs

728: Research (15 decks)

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