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Flashcards in 3: Descriptive research Deck (16)
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1

DR vs experimental research

describing a population OF INTEREST (w/o causality)
Vs
understanding causal effects

2

DR vs surveys

DR includes surveys (USUALLY PAID) n other methods

3

DR answers these 2 Qs:

  • - who are your customers / electors / employees?
  • - what are they doing / thinking in what %?

4

Data can be classified: - By collection purpose - By source

  • - primary (collected for this study) or secondary
  • - internal or external to your org

5

Designing a survey: 4 Qs = 1 what + 3 how's

  1. what to ask? > Prioritize main Qs
  2. how much to ask? < Participants' interests; Time after 5' attention collapses
    > good strat: ask filter Qs (causing branching!) <
  3. how to phrase? > Make it simple (n fun)
  4. how to arrange Qs? > Order from most important (laddering?)

6

Designing a survey: Structure in 4=1+2+1 parts

  1. introduction (inform who is investigating what / why, how long, confidential)
  2. intro Qs: easy > make participants feel confident n committed + screening Qs: to ensure quotas for representation
  3. sensitive n related Qs: real focus of survey, often of sensitive n personal nature
  4. end study: thank n leave contact for further enquiry

7

Designing surveys: 4 aspects to consider reg. Qs (1+2+1)

  • - Q content: only relevant
     
  • - Q response format: closed or open-ended
    > scaling
  • - Q wording > simple
     
  • - Q order > beware of interdependencies

8

Q content: 3-4 aspects to consider (1 + (1 + 1-2) )

  • - how many n which Qs? ~ complexity; consult research lit, eg Marketing Scales Handbook
     
  • - can respondents in yr audience answer yr Q?
    > Include "I don't know"
     
  • - Q needed, acceptable? Eg income
    > use edu or other proxy
  • - will respondents answer truthfully? Social desirability > ask about others in situation

9

Q response format: 2 possibilities

  • - open > explanatory, but more difficult for stat analysis
  • - closed: neutral answer? (w odd-numbered answers)
    > it can be better!

10

Q wording: 6=3+3 aspects to deal with

answerability:

  • - simple n audience-specific language
  • - avoid ambiguity (eg do you exercise regularly?)
  • - avoid burdensome Qs, instead ask memorable Qs w time referents

unbiasedness:

  • - avoid leading Qs (do not add info)
  • - split "double-barrelled" Qs in 2, as they should be
  • - instead of making assumptions (eg of relationships, causal or other, in the Q), split them

11

Q order: problem to solve

- interdependencies < consistency bias
> Separate w other / filler Qs!

12

Collecting data 4 aspects to treat: 2+2

design:

  • who should participate?
    > Set quotas (adjustment by mathematical weighting only works if you are close to target quotas)
  • how often? Cross-sectional vs longitudinal

user-friendliness:

  • may response rate be low?
    > Increase subjects' interest
  • survey works well n in designed time?
    > Pre-test it

13

Sampling: 2 issues to consider

  • - tradeoff: saves money vs asking whole population, but should be representative
  • - quotas help: eg gender according to demography ...but you never know for sure what all aspects to include (use covariates n control for them)

14

Sample types:

  • Cross-sectional
  • multi-cross-sectional
  • longitudinal
  • panel

  • - 1 time 1 sample
  • - 1 time N samples
  • - N times same 1 sample
  • - Ongoing (good for trends but theres panel mortality...)

15

To increase response rate... (1 overarching theme) 4=2+2 pieces of advice

(market yr survey well!)

2 tactical:

  • - time invite / reminder well
  • - keep it short

2 motivational:

  • - mention why, credible affiliation, show who you are
  • - use rewards (lottery for cool prize works best)

16

Pretesting: why, how

  • - on smaller sample: saves you money
  • - check time, wording...