Foundations of
Research
Descriptive research
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© Dr. David J. McKirnan, 2014
The University of Illinois Chicago
McKirnanUIC@gmail.com
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1
2/29/16
Foundations of
Research
Forms of descriptive research
Qualitative or
Observational
Quantitative
Describe an issue via
valid & reliable
numerical measures
Study behavior “in
nature” (high
Simple: frequency
Qualitative
counts of key
behavior
“Blocking” by other
variables
Correlational
research: “what
relates to what”
Complex
modeling
2
ecological validity).




In-depth interviews
Focus (or other)
groups
Textual analysis
Qualitative 
quantitative
Observational


Direct
Unobtrusive
Existing data
Use existing data for
new quantitative (or
qualitative) analyses
Accretion


Study “remnants” of
behavior
Wholly non-reactive
Archival

Use existing data to
test new hypothesis

Typically nonreactive
Foundations of
Research
3
Forms of descriptive research
Quantitative
Qualitative or
Observational
Existing data
Describe an issue via valid
& reliable numerical
measures
Study behavior “in
nature” (high ecological
validity).
Use existing data for new
quantitative (or
qualitative) analyses
Simple:
Qualitative
Accretion
frequency
counts of key
behavior
“Blocking” by
other variables
Correlational
research: “what relates
to what”
Complex modeling

In-depth interviews

Focus (or other) groups

Textual analysis

Qualitative 
quantitative


Direct

Unobtrusive
Wholly non-reactive
Archival

Use existing data to test
new hypothesis

Typically non-reactive
Observational

Study “remnants” of
behavior
Foundations of
Research

4
Examples of descriptive data
Simple description: how much alcohol and
drugs do gay/bisexual men consume?
70
60
 Very high rates of simple use
 Much lower rates of heavy use
 Drugs increasing, alcohol decreasing
1999 -> 2001
50
40
30
20
10
0
Ma
Cra
Alc
C
Me
MD
He
Oth
Da
riju oca
r
yu
t
c
oh
M
o
h
e
k
i
r
.
A
n
sed
ana ine
ol i
nto
xic
atio
n
Any, 6 mo.
McKirnan, D., et al., 2001
community sample
> 3 days / month
Foundations of
Research

5
Examples of descriptive data; blocking variable
More complex description: blocking alcohol &
drug use by ethnicity.
40
% of participants
35
All ps <.01
except
alcohol use.
30
25

Whites show more
alcohol & drug use
on most measures.

Other ethnic
differences vary by
drug.
20
15
10
5
0
An
ys
ub
s
Al
co
tan
ho
l
ce
African-Am., n=430
Ma
rij
u
Ot
h
an
a
er
d
ru
g
Latino, n = 130
Al
-d
ru
g
s
s+
se
x
White, n = 183
2001 Community data: Ethnic differences in frequent (> 3 days/month) drug & alcohol use.
McKirnan, D., et al., 2001
community sample
Foundations of
Examples of descriptive data; Simple correlation of measured variables.
Research

Testing exploratory hypotheses in descriptive data:
Drug use by Quasi - Depression Groups
60

Participants are
blocked (post-hoc)
on a standard
measure of
depression: 0 or 1
symptom v. 3 or more
symptoms.

Men with more
symptoms use all
forms of drugs more
often.
All effects p<.005
% of participants
50
40
30
20
10
0
Any use Any freq.
use
Freq.
Alch.
Intox.
0 - 1 symptom
Freq.
Maj.
Freq.
'Hard'
drugs
> 2 symptoms
0/1 symptoms n = 391, > 2 symptoms n = 289. “Frequent” > 3 days / month.
6
Foundations of
Research
7
Forms of descriptive research
Quantitative
Qualitative or
Observational
Existing data
Describe an issue via valid
& reliable numerical
measures
Study behavior “in
nature” (high ecological
validity).
Use existing data for new
quantitative (or
qualitative) analyses
Simple: frequency
Qualitative
Accretion
counts of key behavior
“Blocking” by other
variables
Correlational

In-depth interviews

Focus (or other) groups

Textual analysis

Qualitative 
quantitative
research: “what
relates to what”
Observational

Direct
Complex
modeling

Unobtrusive


Study “remnants” of
behavior
Wholly non-reactive
Archival

Use existing data to test
new hypothesis

Typically non-reactive
Foundations of
Research

Testing hypotheses with simple correlations:



8
Naturally occurring events: Correlational designs
Brain basis for addiction: test correlation between “sensation
seeking” and drug abuse
Trauma theory of depression: correlate reports of childhood
abuse with scores on a depression measure…
Procedures:


Careful selection of sample to reflect target population
Systematic development of measurements:
 Reliability

Core virtues:



 Validity
“Natural” look at how variables relate
Less control = less reactivity than experimental
designs
Can model very complex phenomena
Foundations of
Research
Does ice cream cause people to drown?
Drownings
This shows a simple
correlation.
How might you interpret
these data?
Ice cream consumption (scoops / day).
9
Foundations of
Research
10
Correlation designs: Drawbacks & fixes
Causality; a simple correlation may confuse cause & effect.
Negative affect
?
Marijuana
consumption
Confounds!; an unmeasured 3rd variable may influence both
observed measures.
Levels of the
neurotransmitter
anandamide?
?
Negative affect
Marijuana
consumption
Dealing with confounds: Use complex measurements or
samples to eliminate alternate hypotheses.
Learn about anandamide.
Foundations of
Research
Complex correlation design: Mothers’ earnings
Does having a child at an earlier age
cause a woman earn less?


Having a 1st child @ age 24 v. 25 correlates
with 10% lower lifetime earnings.

Lower base salary

Smaller raises x earning lifetime
What causes this?

Main hypothesis: Getting pregnant earlier has a big
financial cost, due to the simple burden of motherhood.
Child at an earlier
age.
Slate.com, The Price of Motherhood.
Burden of earlier
motherhood.
Poorer lifetime
earning.
11
Foundations of
Research
12
Motherhood and income.
Is there an alternate hypothesis?
Why else might women who have a
child earlier earn less?
Could a 3rd variable explain both
earlier childbirth and earning
potential?
Alternate
explanation
Child at an earlier
age
Burden of earlier
motherhood
Poorer lifetime
earning.
Foundations of
Research
13
Motherhood and income.
A major alternate hypothesis would be that
certain personal characteristics of women
lead them to both early birth and less $...
…instead of the disadvantage of getting
pregnant earlier in life.
To support the original hypothesis the
researchers tested – and eliminated – two
alternate explanations.
Alternate
explanation
Child at an earlier
age
Burden of earlier
motherhood
Poorer lifetime
earning.
Foundations of
Research
14
Alternate hypothesis 1:
Less personal ambition or skills:
…may lead women to get pregnant earlier and
have less earnings.
Personal
characteristics
(less ambition /
skills)
Decision to have
a child earlier.
Burden of earlier
motherhood
Poorer lifetime
earning.
The researchers tested this alternate hypothesis by
examining different subgroups within their data
Foundations of
Research

15
Test: Compare women who started a family at 24 to women who
tried to start at 24, miscarried, started at 25.



Alternate hypothesis 1:
Women who tried to start at 24 but failed should have the same
characteristics as those who started at 24;
If the alternate hypothesis is correct, this specific comparison should
eliminate the 10% differential.
Data: Comparison still showed a 10% earnings decrement; the
alternate hypothesis was not supported.
Foundations of
Research
16
Alternate hypothesis 2:
Personal importance of motherhood:
Women with strong motherhood values may both
get pregnant early and not value a career.
Personal
importance of
Motherhood
Decision to have
a child earlier.
Burden of earlier
motherhood
Poorer lifetime
earning.
The researchers again used subsets of the data to test if this
explanation is better than the original hypothesis
Foundations of
Research

Alternate hypothesis 2:
Test: women who had been trying to get pregnant since they
were 23. Some succeeded at 24; others at 25.



17
Age of pregnancy was random, so “motherhood value” should be
the same in each group.
If the alternate hypothesis is correct, this specific comparison
should eliminate the 10% differential.
Data: Comparison still showed a 10% difference; 3rd variable
“value” hypothesis was not supported.
Foundations of
Research
18
Bottom line: testing causality in correlational data:
 The simple correlation between age at 1st pregnancy & income
suggests that the simple burden of having children earlier costs.
 Alternate 3rd variable hypotheses question whether the age of 1st
pregnancy really caused lower economic performance.
 It could be women’s job skills or commitment
 …or the value she places on motherhood
 By comparing specific sub-samples from her data…
 ...she was able to test & refute alternate hypotheses about
women’s personal characteristics.
Alternate
explanations
Child at an earlier
age
Burden of earlier
motherhood
Poorer lifetime
earning.
Foundations of
Research
19
Forms of descriptive research
Quantitative
Qualitative or
Observational
Existing data
Describe an issue via valid
& reliable numerical
measures
Study behavior “in
nature” (high ecological
validity).
Use existing data for new
quantitative (or
qualitative) analyses
Simple: frequency
Qualitative
Accretion
counts of key behavior

research: “what relates to
what”
Interviews, focus
groups, textal
analysis
 Qualitative 
quantitative
Complex modeling
Observational
“Blocking” by other
variables
Correlational


Direct

Unobtrusive

Study “remnants” of
behavior
Wholly non-reactive
Archival

Use existing data to test
new hypothesis

Typically non-reactive
Foundations of
Research
Experimental v. Observational research
https://statswithcats.wordpress.com/2015/01/01/how-to-tell-if-correlation-implies-causation/
20
Foundations of
Research

Qualitative research
21
Key feature: Data are unstructured or “natural”




Assess participants’ own thoughts or descriptions
Interview / collect data in participants’ own
environment, using field studies
Less influenced by researchers’ hypotheses or
structured measures
Key uses:

“Ground” research in the every-day reality of people.

Describe the social or physical context of a behavior

Generate hypotheses

Provide a deeper understanding of lab or quantitative
findings.
Foundations of
Research

Approaches to qualitative data
22
Structured / guided description
 Qualitative / semi-structured interviews
 face to face, telephone, “Street intercept”
 Open-ended questions
 Guided analysis of behavior: “deconstruct” an event…
Take me through the last time you drank any alcohol…
What day was it? Time?
Where were you?, what was the place like?
Who were you with … family? Friends? Boy/girl friend? Strangers?
What were you doing / what was going on…
…etc.
Foundations of
Research

Qualitative data: guided description
Approaches to qualitative data
Structured / guided description
 Qualitative / semi-structured interviews
 Focus groups
 Computer programs & raters categorize and count
specific types of responses within the text.

Textual analysis

Use computer or expert raters to analyze existing text


e.g., political writings, therapy transcripts, correspondence
Analyze “found text”

e.g., diary entries, suicide notes
23
Foundations of
Example
of qualitative - quantitative research:
Research
Rafael Diaz’s study of Latino meth use.
Empirical questions:


What % of Latino gay men use stimulants?

Methamphetamine

Cocaine

Other
What does stimulant use “mean” for men? – what are
their motives or understandings?

How does the meaning of drug use differ for meth v.
cocaine?

How do these concepts and attitudes affect drug use?

Sexual or other risks & harms?

Amount of drugs?
24
Foundations of
Research
Diaz study: Qualitative  quantitative approach
1. 2-hour qualitative semi-structured interview with 70
drug-using Latino gay men:
 Detailed qualitative description of drug use & sexual activity




behavior
social contexts
reasons for use
perceived effects
 Narratives on specific episodes of drug use


with and without sexual activity
with and without condom use.
2. Used qualitative findings to develop and test a survey
instrument
 Different dimensions of stimulant use
 Relationship between stimulant use and HIV risk.
3. Administered revised survey to random sample of
Latino gay men (n=300) who reported stimulant use.
25
Foundations of
Research
Diaz study: qualitative findings
Reported positive reasons for using meth / speed:

Energy
We each did a line of crystal because I was feeling sleepy. I
was yawning. It wasn’t that I didn’t want to go out, I think I was
physically just exhausted from the week. It was just long, and
so that kind of gave me a boost of energy.

Youthfulness,
attractiveness
[With crystal] I find that I am no longer pudgy and plump. I feel
that I’m a little bit more physically attractive because I’m not
overweight.
26
Foundations of
Research
Diaz study: qualitative findings, 2, Positive Reasons
Reported sexual effects of meth / speed:



Sexuality
I felt like it rushed to my brain, I felt my skin get hot and I felt
the desire to have sex with whomever was around…
Sexual
disinhibition
I become even more hardcore. Sexual risks and inhibitions are
totally gone. I become empowered in feeling, like I can take on
the world or anyone that f_ _ _ed with me. It can be an
euphoric rush.
Sexual risk
With drugs you start degenerating and you no longer are
satisfied with one person…you want another and you want
more and you want them all at the same time. So I do see a
relationship, drugs do lead to becoming infected with diseases
27
Foundations of
Research
Diaz study: qualitative findings
Reported negative consequences of meth / speed:

Paranoia
That also makes me want to stop because I have been
feeling this horror of someone who is following me, uh…
who wants to kill me or that is hiding but is following me.

Social
isolation
… I was in another world... where at times you lose all
shame, you lose friends, family, you lose... everything.
Sometimes I wouldn't even make a phone call, all I cared
about was getting high and that was it.

Physical
depletion
I feel so gross that I can’t wash it off anymore. It’s like
you feel like this inside dirty, like because there’s no food
in your stomach for the past days, you’ve been just like
running on empty and like you’re really gaunt now
because you’ve been in a constant workout.
28
Diaz study: Quantitative analysis of qualitative findings
Foundations of
Research
Develop conceptual
categories by coders
using the qualitative
data.
Then go back and have the
computer search each interview
for key words to count the % of
men who mentioned each topic
We can then use
quantitative
analyses to test
hypotheses about
differences
between drugs…
29
Foundations of
Diaz
study: Qualitative
findings, 2
Examining
many
categories
of impacts
weQuantitative
can see that:
Research
 Many stimulant users have important negative life effects,
 Significantly more so for meth. than for cocaine.
30
Diaz study: Quantitative phase
Foundations of
Research
1. Using key words from the qualitative phase, create quantitative closed-ended
survey items.
2. Administer the quantitative survey to a much larger sample of men.
3. Use statistical tests to:
a. Ensure the items are reliable and internally valid;
b. Test theory-driven hypotheses about drug use and personal harms.
4. Publish the survey instrument for replicating studies by other researchers.
Meth makes me not feel left out…
Meth makes me feel better
emotionally…
31
Foundations of
Research

Typically uses direct interviews, focus groups..

Structured: specific questions driven by research topic or
hypothesis

Semi-structured: general / probing questions guided by
general topic



Summary: Qualitative research
Unstructured: “personal biography”; completely person
centered.
Important primary data source:

Direct, in-depth measure of behavioral process

Less biased by researcher’s hypothesis than a survey
Important step in quantitative research:

Generate hypothesis or theory of new phenomenon

Produce externally [ecologically] valid qualitative
assessments
32
Foundations of
Research
33
Forms of descriptive research
Quantitative
Qualitative or
Observational
Existing data
Describe an issue via valid
& reliable numerical
measures
Study behavior “in
nature” (high ecological
validity).
Use existing data for new
quantitative (or
qualitative) analyses
Simple: frequency
Qualitative
Accretion
counts of key behavior

“Blocking” by other
variables
Correlational
research: “what relates to
what”
Complex modeling

Interviews, focus
groups, textual analysis
Qualitative 
quantitative
Observational
Direct
 Unobtrusive



Study “remnants” of
behavior
Wholly non-reactive
Archival

Use existing data to test
new hypothesis

Typically non-reactive
Foundations of
Research

Assess behavior directly rather than by participants’ selfreports or recall
Typical data collection is highly reactive: participants know they
are being studied, and react to that

Observational methods are often less (or non-) reactive.


Observational Research
34
Directly observe the social & physical settings or
environments of behavior

Similar to qualitative research:

“ground” a research approach in the every-day reality of people.

describe the social or physical context of a behavior

generate hypotheses

deeper understanding of a set of lab or quantitative findings,
Foundations of
Research
Observational research: methods
35
 Direct observation; visual observation & note taking or
recording.
 Sitting in on classroom discussion, therapy session…
 Ethnographic studies (human or animal)
 Relatively direct data collection
method
 Potentially strong reactive
effects
(Jane Goodall’s Chimpanzee studies were
criticized because she fed and interacted with
her subjects)
Foundations of
Research
Observational research: methods
 Unobtrusive observation; participants unaware of data
collection
 Major advantage: Eliminate reactive effects of data collection
 Less direct data, more difficult to gather & interpret
 One-way mirror & therapy
research
 “Stake out” drug scene
 Focus group observation
 Participant observation; become part of social
phenomenon to describe it
e.g., joining political organization or cult, posing as prostitute (c.f.; Hunter S.
Thomson Hells Angels; NY Times Down Low article here).
 Highly immediate and compelling description
 High potential bias in reporting and description
 Potential ethical concerns
36
Foundations of
Research
37
Forms of descriptive research
Quantitative
Qualitative or
Observational
Existing data
Describe an issue via valid
& reliable numerical
measures
Study behavior “in
nature” (high ecological
validity).
Use existing data for new
quantitative (or
qualitative) analyses
Simple: frequency
Qualitative
Accretion
counts of key behavior

“Blocking” by other
variables
Correlational
research: “what relates to
what”
Complex modeling

Interviews, focus
groups, textual analysis
Qualitative 
quantitative
Observational


Direct
Unobtrusive
Study “remnants”
of behavior
 Non-reactive

Archival
Use existing data
to test new
hypothesis
 Non-reactive

Foundations of
Research
Existing data
38
Accretion; Study remnants of behavior
 Data wholly unobtrusive
Campbell & Webb: Field Museum studies: determine popularity via
linoleum flooring, nose-prints on glass…
HIV prevention studies: # used condoms in “lovers lane” area after a public
health media campaign.
 Indirect; may only partially map onto phenomenon.
Archival; data collected for other purposes
 Often in highly reliable, large & rich data sets
 Provide unbiased correlations, but most be adapted to new
purpose or hypothesis (may not “map on” fully..).
Northern European health records; effectiveness of mammography in
lowering breast cancer
Correlation of suicide rate and publicity about prominent suicides to test
modeling effects.
Foundations of
Research
39
Archival research example.
Archival descriptive data; Standardized Illinois Board
of Ed. drop-out data
Chicago Tribune, 1 in 5 blacks drop out, 11/11/03; full article here.

Very high drop-out rates
in late 90s

Gradual decrease to
2000

Significant increase
again in 2000 – 2001,
coinciding with No Child
Left Behind legislation.

Possible pressure to
raise scores by ushering
lower performing
students out?
Foundations of
Research
40
Archival research example.
Archival descriptive data; Standardized Illinois Board of
Ed. drop-out data
Chicago Tribune, 1 in 5 blacks drop out, 11/11/03; full article here.

Archival data test the
effect of recent
educational policy, even
though they were not
collected for that
purpose.

Cannot clearly answer
the “why?’ question.

Article presents
qualitative data from
individual interviews.

Archival + qualitative
data can be used to
generate important and
testable hypotheses.
Foundations of
Research
Weird archival research example.
Do frustrated people view pornography to feel better?
Data from the 2014 Seattle – Denver Super Bowl.
Baseline
porn traffic
is similar for
the 2 cities
Traffic lessens
in both cities as
the game begins
After the game
traffic is much
higher among
Denver fans
Long after the
game traffic
evens out
As Denver begins
losing badly
traffic increases,
particularly for
Denver fans
41
Foundations of
Research
42
Weird archival research example.
Do frustrated people view pornography to make themselves feel
better? Data from the Super Bowl.
The overall viewing patterns suggest that more fans of a badly losing
team view porn as the game goes on…
 To make themselves feel better?  As a simple distraction?
An alternate hypothesis is
that people in Denver simply
watch more porn.
 This is not plausible:
traffic in the two cities
was the same before and
after the game.
Foundations of
Research
43
Attractiveness & Desirability
What makes a women attractive to men?
On OKCupid…
 Does simple attractiveness lead to more messages?
 Or is there something more complicated?
 The women in these two
pictures get similar
attractiveness ratings, 3.4 v. 3.3
 The picture on the left has a
normal distribution, peaking at
‘4’.
 The picture on the right has a
bimodal distribution: lots of
both ‘1’s and ‘5’s.
Foundations of
Research
44
Attractiveness & Desirability
What makes a women attractive to men?
On OKCupid…
 Simple attractiveness does not by itself lead to more
messages
✓
 The woman with more complex
or diverse ratings gets 2.3
times the average number of
messages…
 The women with less diverse
ç
ç
ratings gets only .8 times the
average.
 This is despite their being
rated as similarly attractive.
Foundations of
Research
45
Attractiveness & Desirability
 This finding is tested more scientifically by deriving the Standard Deviation (S)
of 8 women’s attractiveness ratings, that is, the variance in how she was rated.
 All the women in this chart were about the 80th percentile in attractiveness.
 The amount of variance
in each women’s ratings
(not her overall
attractiveness) is
correlated with the
number of messages
she got.
Foundations of
Research
46
Attractiveness & Desirability
 All the women in this chart were about the 80th percentile in attractiveness.
 Women with higher
deviation scores, i.e.,
both ‘1’s and ‘5’s …
 … elicited more
messages than did
women with more
consistent scores,
i.e., mostly ‘3’s and
‘4’s
 Perhaps simple
attractiveness is not
as interesting as
being challenging.
Foundations of
Research
Archival / “found” data
What is common to these
examples is that the data were
not collected for research.
They stem from tracking
customers, uniform drop-out
rates, etc.
The data are “repurposed” to
answer a research question.
47
Foundations of
Research
48
Overall Descriptive Design Issues
Time frame


Cross sectional

Simultaneous measure of all study variables.

Good for simple description

Major problem for correlations:
Longitudinal




 Causal direction: Which
caused which?
 Major 3rd variable threat (ice
cream and drowning).
Cohort or panel study; follow participants over time.
Best for testing hypotheses; assessing over time helps
determine cause & effect.
With archival data powerful description of behavior (e.g.,
crime rates, health status in population x time).
Case study

Single or multiple n = 1, cross-sectional or longitudinal
Foundations of
Research

Descriptive methods: design issues, 3
Reactive measurement
 Participants (people or animals) react to the knowledge
that they are being measured.
 Represents confound if responses are reaction to
measurement rather than process under study
 Reactive bias increases with..
 Clarity (face validity) of measures
 Face-to-face interview methods
 Often lessened with computer interviews
49
Foundations of
Research
Evaluating our measures: Reliability and Validity.
Reliability
If we are assessing a stable characteristic
(IQ, personality, temperament, core values…)
a good measure will give about the same result
each time we administer it
and for different sections of the measure.
Validity
Our survey or scale must actually measure what
we designed it to.
There are several ways we think about validity,
each getting at a different element…
50
Foundations of
Research

Test - retest;




Reliability
similar responses over time?
Assume stable attribute; e.g., “personality” disposition
If measure is reliable, should show similar scores across time,
e.g., at baseline and after a year.
Split-half; similar responses across item sets?

Assume redundant / converging items or scales.

If scale is reliable, each half should yield similar scores.
Chronbach’s alpha; overall internal reliability

51
Converging items should inter-correlate.
Foundations of
Research

Scale appears to measure what it is designed to

E.g., interview item; “How dependent are you on heroin?”

Simple skill index; assess computer skills by writing program

Intuitively valid; clearly addresses topic

May yield socially desirable responses.
Content validity


Validity
Face validity


Descriptive research:
Assesses all key components of a topic or construct:

e.g., the various components of complex political attitudes…

Mid-term; test all core skills for research design…
Predictive validity

Validly predicts a hypothesized outcome:


e.g., I.Q. is a moderately good predictor of college success, criminality, etc.
A measure may be predictive valid without being face or content valid: the
MMPI.
52
Foundations of
Research

Descriptive research: Validity (2)
53
Construct validity

Test whether the hypothetical construct itself is valid
(differs from other constructs, corresponds to measures or outcomes it
should..).


Test if the Measure addresses the construct it was designed for


E.g.; “anxiety” and “depression” and “anger” may not be separate constructs,
but may all be part of “negative affectivity”.
e.g., measures of social support (“do you have people who care for you”) often
strongly influenced by depression, a separate construct…
“Ecological” validity


Measure corresponds to how the construct “works” in the real
world
External validity of assessment device.
Foundations of
Research
Clicker
Interpret this important data graph
a. More drownings
cause people to eat
ice cream.
b. Sharks like people
who just ate ice
cream.
c. Who knows? It is just
a correlation.
d. Eating ice cream
causes you to drown.
e. In summer people both
eat ice cream and
swim.
54
Foundations of
Research
Qualitative or
Observational
Quantitative
Describe an issue via
valid & reliable
numerical measures
Study behavior “in
nature” (high
Simple: frequency
Qualitative
counts of key
behavior
“Blocking” by other
variables
Correlational
research: “what
relates to what”
Complex
modeling
55
Forms of descriptive research
ecological validity).




In-depth interviews
Focus (or other)
groups
Textual analysis
Qualitative 
quantitative
Observational


Direct
Unobtrusive
Existing data
Use existing data for
new quantitative (or
qualitative) analyses
Accretion


Study “remnants” of
behavior
Wholly non-reactive
Archival

Use existing data to
test new hypothesis

Typically nonreactive
Foundations of
Research
56
Descriptive Research: Overview
Basic design issues:
Time frame



Cross sectional
Longitudinal
Case study
Reliability



Test – retest
Split – half
Alpha (internal)
Validity





Face
Content
Predictive
Construct
Ecological