Laissez les bon temps roulez!!
The Logistics of Constructing a
Research Purpose Statement,
Questions and Hypotheses,
Design, Sample, Measurement,
and Data Analyses Plan
Christopher J. Burant, PhD, Assistant
Professor, School of Nursing Case
Western Reserve University
Cleveland, OH
Co-Director of the GRECC Methodology
Center, the Louis Stokes Cleveland
Veterans Administration Medical Center
What will we learn today?




How to build models to guide your
research.
How to construct a Research purpose
statement, question, and hypotheses.
How to choose the appropriate data
analysis for your research purpose,
question, or hypotheses.
Nuts and Bolts on Design and Sampling
Models can be used to help
develop Research Hypotheses,
Questions and Purpose
Statements
MODEL DEVELOPMENT
IDEA
CONCEPTS
THEORY/MODEL
MEASURES
PURPOSE
DESIGN
Building a Model
• Based on LTE
– Logic
– Theory
– Prior Emperical Evidence
• Build models based on previous models
• Construct own models
– Causal Ordering
– Hypotheses Driven
Using Previous Models
Race/Ethnicity
Socioeconomic
Status
Gender
EXPLANATORY VARIABLES
Social, Political, and
Economic
Conditions and
Policy
Medical Care and Insurance
Health Outcomes
1. Mortality
2. Institutionalization
3. Morbidity (Chronic)
4. Functional
Limitations
5. Self-Rated Health
6. Cognitive Function
7. Depression
Psychosocial Risk Factors
1. Health Behaviors
2. Social Relationships and
Supports
3. Chronic and Acute
Stress
4. Psychological
Dispositions
5. Social Roles and
Productive Activities
Physical/Chemical and Social
Environmental Hazards
8
SES
Education
Occupation
Income
Subjective SES
SES Inequality
Environmental Resources &
Constraints
Neighborhood Factors
Social Capital
Work Situation
Family Environment
Social Support
Discrimination
Race
Gender
Psychological Influences
Resilience/Reserve Capacity
Negative Affect
(anxiety, depression, hostility)
Negative Expectations
Perceived Discriminations
Reactive Responding
Access to
Medical Care
Exposure to
Carcinogens &
Pathogens
Health Outcomes
Health
Cognitive Function
Physical Function
Disease
Health-Related
Behaviors
Disease Trajectories
Recovery
Relapse
Secondary Events
Central Nervous
System & Endocrine
Response
Mortality
Life Course
9
SES
Neighborhood or
Community Hazards
and Supports
Social Conditions (e.g.,
Discrimination) That Are
Correlated With SES
Other Aspects of SES That
Affect Health (e.g., Access to
Medical Care, Nutrition,
Role Models)
STRESS
Behaviors That Impair or
Support Good Health
-Tobacco Use
- Exercise
Biological Changes in
Systems
-Immune System
- Endocrine System
Changes in Illness-Related
Behavior
-Prevention
- Early detection
Health Outcomes
10
Period, Cohort, and Geography
Class, Race, and Gender
School and
Peers
Workplace and
Peers
Family of
Destination’s Social
Capital
Family of
Origin’s Social
Capital
Child’s Social
Capital
Child’s Health Capital
Adult’s
Social
Capital
Adult’s Health
Capital
11
Negative Parental or
Peer Role Models
Poor Childhood
Health Habits
Poor Adult Health
Habits
Poor Adult
Health
Poor Childhood
Socioeconomic
Environment
Inhibits
Development of
Self-Esteem and
Skills
Poor School
Performance
Poor Adult
Environment
Teenage
Parenthood
12
Occupation
Education
Income
Parental
Socioeconomic
Position
Health
Assets/Wealth
Race/Ethnicity
Sex/Gender
Age
13
Introduction
• Models should be developed based on Logic,
•
•
•
Theory and prior Empirical Evidence (LTE)
Variables chosen for the model should be based
on LTE.
When choosing predictors for a model, variables
that should be included should be the same
ones chosen for a regression, such as
sociodemographics, clinical, and psychosocial
relevant variables.
One should also take into account adding all
appropriate confounders to the model.
Causation
“Principle by which cause and effect are
established between two variables. It requires
that there be a sufficient degree of association
(correlation) between the two variables, that
one variable occurs before the other, (that one
variable is clearly the outcome of the other), and
that there be no other reasonable causes for the
outcome. Although in its strictest terms
causation is rarely found, in practice strong
theoretical support can make empirical
estimation of causation possible.” (p. 579)
- Hair, Anderson, Tatham, & Black (1998)
AGE
ETHNICITY
EDUCATION
INCOME
QUALITY OF LIFE
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
Regression representing the predictors of Quality of Life.
AGE
ETHNICITY
EDUCATION
INCOME
QUALITY OF LIFE
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
AGE
ETHNICITY
EDUCATION
INCOME
QUALITY OF LIFE
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
AGE
ETHNICITY
EDUCATION
INCOME
QUALITY OF LIFE
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
AGE
ETHNICITY
EDUCATION
INCOME
QUALITY OF LIFE
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
AGE
ETHNICITY
EDUCATION
INCOME
RELIGIOSITY
QUALITY OF LIFE
WOMAC
CHARLSON
DEPRESSION
AGE
ETHNICITY
RELIGIOSITY
WOMAC
EDUCATION
INCOME
QUALITY OF LIFE
CHARLSON
DEPRESSION
AGE
ETHNICITY
EDUCATION
RELIGIOSITY
WOMAC
CHARLSON
INCOME
QUALITY OF LIFE
DEPRESSION
AGE
ETHNICITY
EDUCATION
INCOME
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
QUALITY OF LIFE
AGE
ETHNICITY
EDUCATION
INCOME
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
QUALITY OF LIFE
SETTING UP THE MODEL
• Models should be developed based on Logic,
Theory or prior Empirical evidence.
• Variables should be temporally ordered with the
most antecedent in time on the left hand side of
the model.
• Create hypotheses based on the bivariate
relationships of the variables in the model a
priori to any analyses.
• Run correlations on all variables. Draw in paths
of all significant relationships. This will be the
initial model.
AGE
ETHNICITY
EDUCATION
INCOME
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
QUALITY OF LIFE
RELIGIOSITY
ETHNICITY
EDUCATION
INCOME
WOMAC
CHARLSON
DEPRESSION
AGE
QUALITY OF LIFE
RELIGIOSITY
WOMAC
EDUCATION
INCOME
CHARLSON
DEPRESSION
AGE
QUALITY OF LIFE
ETHNICITY
INCOME
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
AGE
EDUCATION
ETHNICITY
QUALITY OF LIFE
RELIGIOSITY
WOMAC
CHARLSON
DEPRESSION
AGE
QUALITY OF LIFE
EDUCATION
INCOME
ETHNICITY
WOMAC
CHARLSON
DEPRESSION
AGE
QUALITY OF LIFE
EDUCATION
INCOME
ETHNICITY
RELIGIOSITY
WOMAC
DEPRESSION
AGE
QUALITY OF LIFE
EDUCATION
INCOME
ETHNICITY
CHARLSON
RELIGIOSITY
DEPRESSION
WOMAC
AGE
QUALITY OF LIFE
EDUCATION
INCOME
ETHNICITY
CHARLSON
RELIGIOSITY
WOMAC
AGE
QUALITY OF LIFE
EDUCATION
DEPRESSION
INCOME
ETHNICITY
CHARLSON
RELIGIOSITY
AGE
WOMAC
EDUCATION
QUALITY OF LIFE
INCOME
DEPRESSION
ETHNICITY
RELIGIOSITY
CHARLSON
AGE
WOMAC
EDUCATION
QUALITY OF LIFE
INCOME
DEPRESSION
ETHNICITY
RELIGIOSITY
CHARLSON
AGE
WOMAC
EDUCATION
QUALITY OF LIFE
INCOME
DEPRESSION
ETHNICITY
RELIGIOSITY
CHARLSON
AGE
WOMAC
EDUCATION
QUALITY OF LIFE
INCOME
DEPRESSION
ETHNICITY
RELIGIOSITY
CHARLSON
AGE
WOMAC
EDUCATION
QUALITY OF LIFE
INCOME
DEPRESSION
ETHNICITY
RELIGIOSITY
CHARLSON
AGE
WOMAC
EDUCATION
QUALITY OF LIFE
INCOME
DEPRESSION
ETHNICITY
RELIGIOSITY
CHARLSON
AGE
WOMAC
EDUCATION
QUALITY OF LIFE
INCOME
DEPRESSION
ETHNICITY
RELIGIOSITY
CHARLSON
SOCIODEMOGRAPHIC
FACTORS
PHYSICAL/PSYCHOLOGICAL
FACTORS
AGE
WOMAC
EDUCATION
QUALITY OF LIFE
INCOME
DEPRESSION
ETHNICITY
RELIGIOSITY
CHARLSON
Writing Research Purpose Statements,
Questions, and Hypotheses and
Planning your Analyses

Spell it ALL out… Step by step:
1.
2.
3.
WHAT are your research purpose
statements, questions, or hypotheses?
HOW will the variables be operationalized?
What is YOUR analysis plan?
Writing Research Purpose Statements,
Questions, and Hypotheses and
Planning your Analyses

Spell it ALL out… Step by step:
1.
2.
3.
WHAT are your research purpose
statements, questions, or hypotheses?
HOW will the variables be operationalized?
What is YOUR analysis plan?
Where to start? HERE!!!

What do I use a Hypotheses, a Research
Question, or Research Purpose
Statements?
 It really doesn’t matter. These are very
similar. However, there are subtle
differences. It is really the choice of the
investigator or your dissertation advisor.
Hypotheses
vs.
Research Questions and
Research Purpose Statements
What is a Hypothesis?



Remember back in grade school when
Sister Alberta Einstein told you it was an
“educated guess”. Well that is what it is
an “educated guess”.
It is created based on Logic, Theory, or
Prior Empirical Evidence (LTE).
It is more specific than Research
Questions or Research Purpose
Statements.
What are Hypotheses?


It is more specific than Research
Questions or Research Purpose
Statements.
It includes a direction. (Hey what do you
mean direction?)


To have a quantifying statement such as: “higher or
lower”, “more or less”, “larger or smaller”, “positive or
negative relationship”
This will also allow for a one-tailed statistical
significance test.
An Example of a Hypothesis?
It is hypothesized that in older hospital
patients, those with higher levels of
optimism will have lower levels of
depressive symptoms.
Another way to state this is:
 It is hypothesized that in older hospital
patients, optimism will be negatively
related to depressive symptoms.

Tips for Writing Hypotheses



If you have 2 variables state whether it is
a relationship, a comparison, or predictive
in nature.
State the Independent Predictor Variable
and Dependent Outcome Variable in that
order
State direction in describing variables (e.g.
“more” “less”)
Tips for Writing Hypotheses






Name Populations
Be Specific
Use plural forms to represent groups
Do not use two different terms to refer to the
same variable within a single hypothesis or
across several hypotheses.
Single sentence can have multiple hypotheses.
For multiple related hypotheses use a numbered
list (bullet points).
What are Research Questions
and Research Purpose
Statement?
Why are they lumped together?
 They are conceptually identical.
 They are just stated differently.
 They are more general in nature.

What are Research Questions
and Research Purpose
Statement?



Often used in exploratory, pilot studies
(“sailing unchartered waters”), when
trying to identify relationship or
comparisons.
They are non-directional. They do not
have quantifying statements.
Used for a two-tailed statistical
significance test.
Example of a Research
Questions and a Research
Purpose Statement?

Research Question:


In older hospital patients, how is their level of
optimism related to their level of depressive
symptoms?
Research Purpose statement:

The purpose of this research is to identify
how levels of optimism are related to levels of
depressive symptom in older hospital patients.
Tips for writing Research
Questions and Research
Purpose Statements?

Do not state a research questions that
have a “yes” or “no” answer


In older hospital patients, is their level of
optimism related to their level of depressive
symptoms?
If you have 2 variables state whether it is
a relationship, a comparison, or predictive
in nature.
Tips for writing Research
Questions and Research
Purpose Statements?




State the Independent Predictor Variable
and Dependent Outcome Variable in that
order
Name Populations
Use plural forms to represent groups
Recommended for no relationships (e.g.,
for descriptives), qualitative, and new or
contradictory (to previous research) topic
Tips for writing Research
Questions and Research
Purpose Statements?




Use plural forms to represent groups
Do not use two different terms to refer to the
same variable within a single Research
Question/Purpose or across several Research
Question/Purposes.
Single sentence can have multiple hypotheses.
For multiple related Research Question/Purposes
use a numbered list (bullet points).
Where to start? HERE!!!

What QUESTIONS are you trying to answer?
 Are
you testing:
 Differences
between groups?
 Relationships between variables?
 A variable predicting another
variable?
 Changes over time?
 Univariate descriptives of variables
Writing a Methodologically Sound
Research Proposal

Spell it ALL out… Step by step:
1.
2.
3.
WHAT are your research purpose
statements, questions, or hypotheses?
HOW will the variables be operationalized?
What is YOUR analysis plan?
Choosing Instrumentation

Should I develop a new tool or use an
existing tool?

Instrument development can be a tedious
undertaking;
Reliability Issues…
 Validity Issues…
 Factor analysis…

Benefits of Using Existing
Instruments

Literature to draw upon


Effect size information
Readily available reliability/validity
information


Cronbach’s alpha
Details on psychometric properties
Still More Benefits!
(get the idea? Try and AVOID survey development!)

Judgmental Validity



Criterion Related Validity



Content Validity
Face Validity
Predictive
Concurrent
Reliability issues related to Validity

Consistency of results
Survey Development








Focus Groups
Content Validity
Face Validity
Piloting testing
EFA
CFA
Convergent and divergent validity
Really hard stuff…
Writing Research Purpose Statements,
Questions, and Hypotheses and
Planning your Analyses

Spell it ALL out… Step by step:
1.
2.
3.
WHAT are your research purpose
statements, questions, or hypotheses?
HOW will the variables be operationalized?
What is YOUR analysis plan?
Thinking through the process…

Once you narrow your research
hypotheses, questions, or purpose
statements choose the proper tool to
answer them…
Levels of Measurement
(remember this stuff????)
 Broadly speaking, data take 2 forms

Categorical


Nominal
Continuous



Ordinal
Interval
Ratio
A new look at the variables…

IPV: Independent Predictor Variable




Stimuli
Cause
Treatment
DOV: Dependent Outcome Variable



Outcome
Effect
Response
Thinking through the
process…

Once you narrow your research hypotheses,
questions, and purpose statements choose the
proper tool to answer them…
 Testing group differences?
If your IPVs and DOVs are all CATEGORICAL?
 Independent Predictor Variable= Gender M/F



Dependent Outcome Variable=Depressed? Y/N?
[CES-D score <16 and >16]


Categorical (dichotomized)
Categorical (dichotomized)
Chi Square…
The Chi Square

What is a GOOD Research Question that
should be analyzed with a Chi Square ?

Among elderly patients, what are the
differences by gender in being diagnosed as
Depressed?
The Chi Square

What is a GOOD Research Purpose
statement that should be analyzed with a
Chi Square ?

The purpose of this research is to identify the
differences by gender in being diagnosed as
Depressed within an elderly patients sample.
The Chi Square

What is a GOOD Research Hypotheses
thath should be analyzed with a Chi
Square ?

It is hypothesized that among elderly patients
females will be more likely to be diagnosed
with Depression as compare to males
Thinking through the process…

What Analysis would you run if your Research
Hypotheses, Question or Purpose Statement had
the following:

Dichotomous Independent Predictor Variable

2 Groups



Continuous Dependent Outcome Variable

A composite scale score



Male/female
Intervention/control
Depression Scale
GPA
I am sure you guessed an Independent
Samples T-test.
The Independent Samples
T Test

So what would be a GOOD Research Question
that should be analyzed with an Independent
Samples T Test?

Same as the Chi Square question without the cut point!

Among elderly patients, what are the differences by gender
(IPV=M/F) on their score of depressive symptoms? (DOV=
Score on a CES-D {raw score of summed items 0-60…etc.})
The Independent Samples
T Test

So what would be a GOOD Research Purpose
statement that should be analyzed with an
Independent Samples T Test?

Same as the Chi Square question without the cut point!

The purpose of this research is to identify the differences by
gender (IPV=M/F) on depressive symptoms within an elderly
patients sample? (DOV= Score on a CES-D {raw score of
summed items 0-60…etc.})
The Independent Samples
T Test

So what would be a GOOD Research Hypotheses
that should be analyzed with an Independent
Samples T Test?

Same as the Chi Square question without the cut point!

It is hypothesized that among elderly patients, Females will
have higher scores of Depressive Symptoms as compared to
Males. (DOV= Score on a CES-D {raw score of summed items
0-60…etc.})
Thinking through the process…

What Analysis would you run if your
Research Hypotheses, Question or
Purpose Statement was:

Comparing 2 continuous level
variables…change over time…
A composite score, pre and post intervention
 A mom’s composite score with her child’s
composite score


You guessed it a Paired T-Test.
The Paired T Test

So what would be a GOOD Research Question
that should be analyzed with a Paired T-test?

Among elderly patients, how do their scores of
depressive symptoms change from pre-treatment to
post-treatment?
The Paired T Test

So what would be a GOOD Research Purpose
statement that should be analyzed with a Paired
T-test?

The purpose of this research is to identify among
elderly patients the change in their scores of
depressive symptoms from pre-treatment to posttreatment.
The Paired T Test

So what would be a GOOD Research Hypotheses
that should be analyzed with a Paired T-test?

It is hypothesized that among elderly patients, the
change in their scores of depressive symptoms from
pre-treatment to post-treatment will decrease.
Thinking through the process…

What Analysis would you run if your
Research Hypotheses, Question or
Purpose Statement was:

Comparing 3 or more continuous level
variables…change over time…


A composite score, From Baseline to TIME 2
You are right again a Repeated Measures
ANOVA
Repeated Measures ANOVA

So what would be a GOOD Research Question
that should be analyzed with a Repeated
Measures ANOVA?

Among elderly patients, how do their scores of
depressive symptoms change from Admit to
Discharge to one month post-hospitalization? (You
see 3 time periods)
Repeated Measures ANOVA

So what would be a GOOD Research Purpose
statement that should be analyzed with a
Repeated Measures ANOVA?

The purpose of this research is to identify among
elderly patients the change in their scores of
depressive symptoms from Admit to Discharge to one
month post-hospitalization?
Repeated Measures ANOVA

So what would be a GOOD Research Hypotheses
that should be analyzed with a Repeated
Measures ANOVA?

It is hypothesized that among elderly patients, the
change in their scores of depressive symptoms from
from Admit to Discharge to one month posthospitalization will decrease over time?
Thinking through the process…

What Analysis would you run if your Research
Hypotheses, Question or Purpose Statement had
the following:

Categorical Independent Predictor Variable

2 or more Groups (preferably 3 or more)


Continuous Dependent Outcome Variable

A composite scale score



IPV=MSN, DNP or PhD? (grouping variable)
DOV=Quality of life scale (0-100)
Depression Scale
You are correct a 1-Way ANOVA
1-Way ANOVA

So what would be a GOOD Research Question
that should be analyzed with a 1–Way ANOVA?

Which group of advanced-degreed nurses score
highest on a Quality of Life measure?
1-Way ANOVA

So what would be a GOOD Research Purpose
Statement that should be analyzed with a 1–
Way ANOVA?

The purpose of this research is to identify which
group of advanced-degreed nurses score highest
on a Quality of Life measure?
1-Way ANOVA

So what would be a GOOD Research Hypotheses
that should be analyzed with a 1–Way ANOVA?

It is hypothesized that nurses with a PhD score
highest on a Quality of Life measure as compared
to nurses with an MSN or a DNP?
Thinking through the process…

What Analysis would you run if your Research
Hypotheses, Question or Purpose Statement had
the following:

Two continuous variables and you wanted to test the
relationship between the two variables.



Depressive Symptoms
Quality of Life
Correct a Correlation
Correlation

So what would be a GOOD Research Question
that should be analyzed with a Pearson r
correlation?

Among elderly patients, what is the relationship
between depression scores and quality of life
scores?

Each variable is continuous.
Correlation

So what would be a GOOD Research Question
that should be analyzed with a Pearson r
correlation?

The purpose of the research is to identify the
relationship between depression scores and a
quality of life scores within a sample of elderly
patients?
Correlation

So what would be a GOOD Research Hypotheses
that should be analyzed with a Pearson r
correlation?

It is hypothesized that among elderly patients,
those with higher depression scores will have
lower quality of life scores.
Thinking through the process…

What Analysis would you run if your Research
Hypotheses, Question or Purpose Statement had
the following:

Continuous Independent Predictor Variable


Depression Scale
Continuous Dependent Outcome Variable
Quality of Life
Casual order (IPV/DOV) often needs to be determined
chronologically. Which happens first?
Use terms like: predicts, impacts, affects, causes, contribute to




Right again a Regression
Regression

So what would be a GOOD Research Question
that should be analyzed with a Regression?

Among elderly patients, do depression scores
impact quality of life scores?

IPV and DOV variables are continuous.
Regression

So what would be a GOOD Research Question
that should be analyzed with a regression?

The purpose of the research is to identify if
depression scores impact quality of life scores
within a sample of elderly patients?
Regression

So what would be a GOOD Research Hypotheses
that should be analyzed with a regression?

It is hypothesized that among elderly patients,
higher depression scores will contribute to lower
quality of life scores.
Thinking through the process…

What Analysis would you run if your
Research Hypotheses, Question or
Purpose Statement was:

Describing a variable
Continuous (e.g., A1C levels)
 Categorical (e.g., Political Affiliation)


You guessed it univariate descriptive statistics
for continuous (e.g., Means, SD, & range) and
Categorical (Frequencies and Percentages)
Univariate Descriptive Statistics

So what would be a GOOD Research Question
that should be analyzed with univariate
descriptive statistics?

Among diabetic patients, what is their mean A1C
level?
Univariate Descriptive Statistics

So what would be a GOOD Research Purpose
statement that should be analyzed with
univariate descriptive statistics?

The purpose of the research is to identify the
mean A1C level among diabetic patients.
Univariate Descriptive Statistics

So what would be a GOOD Research Hypothesis
that should be analyzed with univariate
descriptive statistics?

It is hypothesized that among diabetic patients the
mean A1C level is above 7%.
Now that you have your
research question, purpose
statement or hypotheses, you
have to decide on your research
design.
Are you looking for an experimental
or a non-experimental design?

Experimental – researchers give treatment
and observe changes in behaviors.

Could be with a control vs. treatment group
design
R O X O
R O
O

Could be just with a treatment group
O X O
Are you looking for an experimental
or a non-experimental design?

Non-Experimental – researchers do not
give treatments and describe subjects as
they naturally exist without experimental
treatments.


Causal Comparative Study – target group (
e.g., with an illness) vs. control group (e.g.,
absent of illness) and match by characteristics
Other examples: surveys, case studies,
longitudinal, correlational, qualitative, chart
reviews
Hey Chris,
Can you touch base on
Sampling
You Betcha, I Can
Types of Sampling


Simple random sampling – every member
of population has equal chance of being
included in sample.
Samples of convenience – Used with hard
to get samples, identifying support for
new theory. Often used for pilot work
Types of Sampling


Stratified random sampling – divide
sample into strata. Match % of sample
with % in population. Reduces sampling
bias
Cluster Sampling – Draws groups instead
of individuals (e.g., Churches, schools)
Types of Sampling


Purposive sampling – select from
individuals whom will be a good sources of
information (e.g., caregivers)
Snowball Sampling – locate participants
who are hard to find from other like
subjects.
Now you are on the right track!

You have your (at least rough) Research
Question, Research purpose statement, or
Research Hypotheses!
Now you are on the right track!


You have your (at least rough) Research
Question, Research purpose statement, or
Research Hypotheses!
You have operationalized your variables of
interest!
Now you are on the right track!



You have your (at least rough) Research
Question, Research purpose statement, or
Research Hypotheses!
You have operationalized your variables of
interest!
You have chosen your statistics to answer
them…
Now you are on the right track!




You have your (at least rough) Research
Question, Research purpose statement, or
Research Hypotheses!
You have operationalized your variables of
interest!
You have chosen your statistics to answer
them…
You have learned a little on design and
sampling.
Now, you have enough
information to be dangerous.
Resources Worth Owning

Patten: Proposing Empirical Research: A guide to the
Fundamentals.


Patten: Understanding Research Methods.


A REALLY nice primer
Great overview of Research Methods
Pyrczak and Bruce: Writing Empirical Research Reports

Very nice companion piece