Post on 17-Jan-2016
description
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Procedural Analysis or structured approach
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Procedural Analysis or structured approach Sometimes known as Analytic Induction
Used more commonly in evaluation and policy studies.
Uses a set of procedures as a way of establishing explanations and causal links
The approach tends to assume that meanings are transparent, obvious and unambiguous, and instead concentrates on validating explanations.
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References Robson, C. (1993) Real World Research (First
Ed) Yin, R. (1994) Case Study Research: Design
and Method Bryman,A (2008) Social Research Methods
pp. 539-541. Gomm, R, Hammersley, M, & Foster P (eds)
(2000) Case Study Method – See esp. chapter 8.
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Reasons for structured approach
Deficiencies in the analyst1. Data overload (too much to remember, process
etc.)2. First Impressions (bias to first things read)3. Information availability (easy information gets
more attention)4. Positive instances (stress what confirms ideas)5. Internal consistency (discount the novel)6. Uneven reliability (not all sources equally good)
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Reasons for structured approach 2
7. Missing information (don’t try hard enough to fill gaps)8. Revision of hypotheses (over- or under- react to new
info)9. Fictional base (compare with assumed average)10. Confidence in judgement (too much when made)11. Non-occurrence (seen as evidence for strong
correlation)12. Inconsistency (different interpretations of same data)All this means threats to: reliability and generalizability validity
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Especially for validity
History (background changes during study)
Mortality (people dropping out unrepresentative)
Maturation (people changed by the study) ambiguity about causal direction (unclear
what causes what)
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For generalizability
Limited to: group studied setting it took place in time it happened particular constructs of the group
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Pattern Matching
Compare an empirical based pattern with a predicted one (and with several alternatives)
Looking for causal connections If patterns coincide this strengthens
internal validity.
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1. Non-equivalent dependent variables as a pattern
Like quasi-experimental designs: hypothesis testing
Use where theory suggests multiple dependent variables or a variety of outcomes.
If for each outcome, initially predicted outcomes are found and alternative are not found (i.e. no threats to validity found) then can infer causal influence.
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e.g. Effects of decentralized approach to office automation
from Yin
Decentralization theory suggests 4 outcomes Employees create new applications Traditional supervisory links are threatened Organizational conflicts increase Productivity will increase
If results in the case are as these 4 predictions then draw conclusions that it is decentralization that caused these effects.
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Replication Literal replication = more cases of the same
kind Theoretical replication = case where automation
is centralized. Then there will be 4 different effects. Causal link is confirmed if this is what happened.
BUT must be aware of threats to validity. Identify and eliminate all reasonable threats.
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2. Rival Explanations
Test contrasting theories i.e. we have several independent
variables or starting circumstances. Examine cases for characteristics of the precursors to see which fits best.
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Problems with pattern matching
How do we know a pattern fits? Matter of judgement.
Need to balance overly restrictive application of pattern matching with too loose a match.
“eyeballing” the pattern is good enough.
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Analytic Induction
A.k.a. Explanation building i.e. build up and confirm a set of causal
links between events, actions etc in the case.
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Analytic Induction process
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Problems Need constantly to entertain other plausible,
rival explanations. = HARD WORK With each iteration, there may be a drift from
the original question or lots of work to re-analyze data.
Only establishes sufficient conditions (not necessary)
No guide as to how many negative cases are needed for validity.
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Time series
Like time series in a quasi experiment.
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Problem Changes may have no clear start or end point.
Must compare1. Theoretically significant trend predicted before
research,2. Rival trend predicted before research,3. Any trend based on artefacts or threats to
internal validity.
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Chronologies
Look for sequences and patterns of events.e.g. some events always happen before others,
and the reverse is impossible some events always follow others, some events always follow others after the
passage of time some time periods differ from other time
periods in the type of events that occur.