The document provides an overview of quantitative research designs. It defines quantitative research as using measured variables and numerical data to describe or test relationships among variables. The document outlines key concepts in research design including definition, elements of a strong design like controlling variables, and types of designs. It discusses descriptive, correlational, quasi-experimental, and experimental designs. Descriptive designs provide a picture of natural situations while quasi-experimental and experimental designs examine causality. Specific designs are defined within each category like comparative descriptive, longitudinal, predictive correlational, non-equivalent groups, and factorial designs. Repeated measures and assumptions are also covered.

1. 1
Quantitative
Research Designs
Presented by
Dr. Fuad Abuadas
PhD, MSN, CNS, RN

2. 2
Outlines
 Introduction
 Definition of Design
 Concepts Important to Design
 Elements of a Good Design
 Triangulation
 Descriptive study designs
 Correlation study designs
 Quasi-experimental study designs
 Experimental study designs
 Other Research Designs
 Conclusion
 References

3. Quantitative Research
 Used to describe or test relationships among variables or to
evaluate the effect of one variable on another.
 Variables are “measured” using standard data collection tools
and data are numerical (numbers).
Qualitative Research
 Used when little is known about a phenomenon.
 Focused on developing a rich, holistic description of
phenomena.
 Data are non numerical (i.e., dialogue, observation, etc.).
APPROACHES TO
RESEARCH IN NURSING

4. NURSING SCIENCE USES VARIOUS
RESEARCH METHODOLOGIES
4
Qualitative
 Understanding
 Interview / observation
 Discovering frameworks
 Textual (words)
 Theory generating
 Quality of participant is more
important than sample size
 Selection of best participants
 Subjective
 Intuitive
 Embedded knowledge
Quantitative
 Prediction
 Survey/questionnaires/Intervention
 Existing frameworks
 Numerical
 Theory testing
 Sample size is important
 Randomisation of Participants
 Objective
 Public

5. 5
Research Design
All researchers should be aware of the
basic strategies used to develop evidence
that the results of their study will be
accurate and interpretable.
(Polit & Beck, 2016)
This can be achieved using the
appropriate research design.
(Polit & Beck, 2016)

6. 6
Definition of Research Design
•It is a blueprint or detailed plan for conducting the
study that maximizes control over factors that could
interfere with the validity of the findings (Burns &
Grove, 2015).
•Research design is the overall plan for addressing a
research question, including specifications for
enhancing the study’s integrity (polit & Beck,
2016).

7. 7
Research Design Vs Research
Methodology
 Research Design includes structures
within which the study is implemented.
 (Burns & Grove, 2015).
•Research methodology is the entire
strategy for the study, from identification
of the problem to final plans for data
collection.
(Burns & Grove, 2015).

8. 8
Elements of a Strong Design
 Controlling the environment.
 Controlling equivalence of subjects and
groups.
 Control groups.
 Controlling the treatment.
 Counterbalancing.
 Controlling measurement.
 Controlling extraneous variables.
(Burns & Grove, 2005).

9. 9
Controlling the Environment: Study setting
should be consistent for all participants and
control extraneous variables.
Controlling Equivalence of Subjects and Groups:
This is achieved by defining sampling criteria,
random sampling, random assignment to groups,
and pretest and posttest measurements.
Controlling the Treatment: Using strategies to
ensure consistency in implementing the treatment.
(Burns & Grove, 2005).

10. 10
(Burns & Grove, 2005)
Controlling Measurement: Measures must have
documented validity and reliability. In addition, data
collectors must be trained for and observed for
consistency.
•Controlling Extraneous Variables
•Extraneous variables are not included in design, but
could explain some of the variance in measurement of
the study variables.
•Extraneous variables commonly encountered are age,
education, gender, social class, severity of illness, and
attitudes.

11. 11
Types of Quantitative Research
Designs
There are four broad
categories for quantitative
research design (Burns &
Grove, 2015)
 Descriptive designs
 Correlational designs
 Quasi-experimental designs
 Experimental designs
There are four broad
categories for quantitative
research design (Polit &
Beck, 2016)
 Non-experimental designs
 Pre-experimental designs
 Quasi-experimental designs
 Experimental designs

12. 12
•Descriptive Study Designs

13. 13
Descriptive Study Designs
(Burns & Grove, 2015)
Provide a picture of situations as they naturally happen.
.
May be used to develop a theory, identify problems in current
practice or making judgments.
•No manipulation of variables is involved.
•No dependent and independent variables.
•No attempt to establish causality.
The relationship between variables can be identified, but types
and degree of relationships is not the primary concern.

14. 14
Types of Descriptive Study Designs
 Typical descriptive study designs
 Comparative descriptive study design
 Time-dimensional designs
Longitudinal designs
Cross-sectional designs
Trend designs
Event-partitioning designs
 Case study designs
(Burns & Grove, 2015)

15. 15
1. A Typical Descriptive Design
•Clarification •Measurement •Description •Interpretation
•Phenomenon
of Interest
•Description of
Variable 1
•Description of
Variable 2
•Description of
Variable 3
•Description of
•Variable 4
•Variable 1
•Variable 2
•Variable 4
•Variable 3
•Interpretation
of Meaning
•Development of
Hypotheses
•15
(Burns & Grove, 2015)

16. 16
A Typical Descriptive Design
•Clarification •Measurement •Description •Interpretation
•Phenomenon
of Interest
•Description of
Job related
stressors
•Job Related
•stressors
•Interpretation
of Meaning
•Development of
Hypotheses
•16
(Burns & Grove, 2015)

17. 17
2. A Comparative Descriptive Design
•Group I
{variables
measured}
•Group II
{variables
measured}
•Describe
•Interpretation
of Meaning
•Comparison of
Groups on
Selected Variables
•Describe •Development
of Hypotheses
•17
(Burns & Grove, 2015)

18. 18
2. A Comparative Descriptive Design
•Group I (Military Hospital)
•Describe
•Interpretation
of Meaning
•Comparison of patient
satisfaction between
Military & governmental
hospitals
•Describe •Development
of Hypotheses
•18
(Burns & Grove, 2015)
Patient
satisfaction
•Group iI (Governmental Hospital)
Patient
satisfaction

19. 19
Time-dimensional Designs
 According to Burns and Grove (2015), There are
four major types of descriptive time-dimensional
design:
 Longitudinal Designs
 Cross-Sectional Designs
 Trend designs
 Event-practitioning design

20. 20
Time-dimensional Designs
(Burns & Grove, 2015)
•Longitudinal Designs: data are collected about the same
subject at more than one point in time.
•Cross-Sectional Designs: examine group of subjects in
various stages of development simultaneously with the intent
to describe changes in phenomenon across stages.
•Trend Designs: Different samples are selected at repeated
intervals with respect to some phenomenon from the same
population.
•Event-partitioning Design: a merge of the cross-sectional or
longitudinal and trend designs.
•

21. 21
•Correlational Study Designs

22. 22
Correlational Study Designs
(Burns & Grove, 2015)
•Correlation study designs examine the
relationships among variables.
•In correlation designs, a large variance in the
variable scores is necessary to determine the
existence of a relationship.

23. 23
Determining Type of Correlational Design
•Each of these designs is based on relationships
among variables, and the variable would be
measured in one sample of subjects.
•Descriptive correlational design is used when the
researcher lacks information about the possible
relationships among the variables and is conducting
the study to identify possible relationships.

24. 24
1. Descriptive Correlational Study
Designs
•Research
•Variable
•1
•Research
•Variable
•2
•Description
•of variable •Interpretation
•of Meaning
•Examination of
•Relationship
•Description
•of variable •Development
•of Hypotheses
•Measurement
•24
(Burns & Grove, 2015)

25. 25
Descriptive Correlational Study
Designs
•Job related
stressors
•Job
Satisfaction
•Description
•of variable •Interpretation
•of Meaning
•Examination of
•Relationship
•Description
•of variable •Development
•of Hypotheses
•Measurement
•25
(Burns & Grove, 2015)

26. 26
2. A Predictive Correlational Design
•Value
of
Intercept
•Value of
Independent
Variable
1
•Value of
Independent
Variable
2
•Predicted
Value of
Dependent
Variable
+ + =
•Predictive correlational designs are used when the
researcher has evidence from the empirical and
theoretical literature indicating relationships among the
variables to the extent that researchers can identify
possible independent and dependent variables.

27. 27
•Quasi-experimental Designs

28. 28
•The purpose of quasi-experimental and experimental
designs is to examine causality.
•Quasi-experimental designs provide alternative means
of examining causality in situations not conducive to
experimental controls.
•In these situations, at least one of the three
components of true experimental design
(randomization, comparison groups, and manipulation
of the treatment) is lacking.
Quasi-experimental Designs
(Burns & Grove, 2015)

29. 29
Types of Quasi-experimental Designs
Nonequivalent Comparison Group Studies
 One-group posttest-only designs
 posttest-only designs with comparison group
 One-group Pre-test Post-test designs
 Pre-test and Post-test designs with a comparison group
 Pre-test and Post-test designs with a two comparison treatments
 Pre-test and Post-test designs with a two comparison treatments
and standard or routine care group
 Pre-test and Post-test designs with a reversed treatment
Interrupted Time-series Designs
 Simple Interrupted time-series designs
 Interrupted time-series designs with a comparison group
 Interrupted time-series designs with multiple treatments.
(Burns & Grove, 2015)

30. 30
Nonequivalent Comparison Group
Studies
(Burns & Grove, 2015).
•A comparison group is one in which the groups are
not selected by random means.
• Selection is a threat to validity because participants
are not selected randomly.

31. 31
•Experimental Study Designs

32. 32
Experimental Study Designs
 Experimental post-test only comparison group
design.
 Experimental Pretest and post-test comparison
group design (Classic experimental design)
 Factorial designs
 Crossover or counterbalancing
 Solomon 4 groups design.

33. 33
Repeated Measures
Note: Understanding this concept might
help students understand the concept of
pre-post testing in research design.

34. 34
Repeated Measures
 Repeated measures’ is a term used when the same
entities participate in all conditions of an experiment or
provide data at multiple time points (e.g., T0 (Baseline),
T1 (Post-intervention), and T2 (Follow-up).
 It is used to analyzes groups of related dependent
(outcome) variables that represent different
measurements of the same attribute.
 Types of Repeated Measures ANOVA
 One-way repeated-measures designs
 Two ways repeated measures designs

35. 35
The Define Factor(s) dialog box for
repeated-measures ANOVA

36. 36
One-way repeated-measures
designs
 One-way repeated-measures designs compares several
means, when those means come from the same entities
(e.g., same participants); for example, if you measured
people’s statistical ability each month over a year-long
course.
 Note: When you have three or more repeated-measures
conditions there is an additional assumption:
sphericity.
 You can test for sphericity using Mauchly’s test, but it is
better to always adjust for the departure from sphericity in
the data.

37. 37
Two ways repeated measures
 Two-way repeated-measures designs compare means
when there are two predictor (independent) variables,
and the same entities have been used in all conditions.
 Note: You can test the assumption of sphericity when
you have three or more repeated-measures conditions
with Mauchly’s test, but a better approach is to
routinely interpret F-statistics that have been corrected
for the amount by which the data are not spherical.

38. 38
Other possible Assumptions to be met
 Assumption of homoscedasticity
 Assumption of singularity
 Assumption of multicollinearity
 Adequacy of samples
 Examination of correlation

39. 39
Post-test-only control group design.
Group
assignment
Measurement
or observation
Application of
independent
variable
Experimental
Intervention
No Intervention
or Placebo

40. 40
Pretest-posttest control group design
Group
assignment
Measurement
or observation
Application of
independent
variable
Measurement
or observation
Experimental
Intervention
No
Intervention
or Placebo

41. 41
Two-group pretest-posttest design
Experimental
Intervention 1
Experimental
Intervention 2
or Standard Care
Group
assignment
Measurement
or observation
Application of
independent
variable
Measurement
or observation

42. 42
Multigroup pretest-posttest control
group design
Experimental
Intervention 1
Experimental
Intervention 2
No Intervention
or Placebo
Group
assignment
Measurement
or observation
Application of
independent
variable
Measurement
or observation

43. 43
Factorial Design
When an experiment has two or more independent
variables it is known as a factorial design (because, as
we have seen, independent variables are sometimes
referred to as factors).
Types of Factorial Design
1. Independent factorial design: There are several
independent variables or predictors and each has been
measured using different entities (between groups).
2. Repeated-measures (related) factorial design:
Several independent variables or predictors have been
measured, but the same entities have been used in all
conditions
3. Mixed design: Several independent variables or
predictors have been measured; some have been
measured with different entities, whereas others used
the same entities.