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Chapter 8

Clarifying Quantitative Research Designs

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Research Design

Blueprint or detailed plan for conducting a study

Purpose, review of literature, and framework provide the basis for the design

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Study Purpose

To describe variables To examine relationships To determine differences To test a treatment To provide a base of evidence for practice A combination of above

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Design Characteristics

Maximizes control over factors to increase validity of the findings

Guides the researcher in planning and implementing a study

Not specific to a particular study, but linked to other steps of the research process

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Concepts Relevant to Design

Causality Multicausality Probability Bias Control Manipulation

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Causality

There is a cause-and-effect relationship between the variables.

The simplest view is one independent variable causing a change in one dependent variable.

Independent variable (X) causes Y (a change in the dependent variable).

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Multicausality

There is a cause-and-effect relationship between interrelating variables.

There are multiple independent variables causing a change in the dependent variable.

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Causality: A B

Pressure Ulcer

Multicausality:Years smokingHigh-fat diet Heart diseaseLimited exercise

Diagram of Causality and Multicausality

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Probability

The likelihood of accurately predicting an event

Variations in variables occur. Is there relative causality? Therefore, what is the likelihood that a

specific cause will result in a specific effect?

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Bias

The slanting of findings away from the truth Bias distorts the findings. Research designs should be developed to

reduce the likelihood of bias or to control for it.

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Potential Causes of Bias in Designs

Researchers Components of the environment and/or

setting Individual subjects and/or sample How groups were formed Measurement tools Data collection process Data and duration of study (maturation) Statistical tests and analysis interpretation

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Control

Implemented throughout the design Improved accuracy of findings Increased control in quasi-experimental

research Greatest in experimental research

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Manipulation

Implementation of a treatment or intervention The independent variable is controlled. Must be careful to avoid introduction of bias

into the study Usually done only in quasi-experimental and

experimental designs

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Elements of a Strong Design

Controlling environment: selection of study setting

Controlling equivalence of subjects and groups

Controlling treatment (Tx) Controlling measurement Controlling extraneous variables

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Critiquing a Study Design

Was the type of design identified? Was the study design linked to the purpose

and/or objectives, questions, or hypotheses? Were all variables manipulated or measured?

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Critiquing a Study Design (cont’d)

If the study included a treatment, was it clearly described and consistently implemented?

Were extraneous variables identified and controlled?

What were threats to design validity in study?

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Critiquing a Study Design (cont’d)

Was a pilot study performed? What was reason for pilot and the outcome?

Study feasibility Refine design or treatment Examine validity and reliability of measurement

methods

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Critiquing a Study Design (cont’d)

How adequate was the manipulation? What elements should have been

manipulated to improve the validity of the findings?

Based on your assessment of the adequacy of the design, how valid are the findings?

Is there another reasonable (valid) explanation (rival hypothesis) for the study findings other than that proposed by the researcher?

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Critiquing a Study Design (cont’d)

Identify elements controlled in the study. Identify possible sources of bias. Are there elements that could have been

controlled to improve the study design? What elements of the design were

manipulated and how were they manipulated?

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Types of Quantitative Research Designs

Descriptive study designs Correlational study designs Quasi-experimental study designs Experimental study designs

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Diagramming the Design

Clarifies variables to be measured or manipulated

Indicates focus of study: description, relationships, differences, and/or testing a treatment

Identifies data collection process: time for study, treatment implementation, measurement of variables

Provides direction to data analysis

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Descriptive Study Designs

Typical descriptive design Comparative descriptive design Case study design

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Typical Descriptive Design

Most commonly used design Examines characteristics of a single sample Identifies phenomenon, variables, conceptual

and operational definitions, and describes definitions

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Comparative Descriptive Design

Examines differences in variables in two or more groups that occur naturally in a setting

Results obtained from these analyses are frequently not generalizable to a population

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Case Study Design

Exploration of single unit of study (i.e., family, group, or community)

Even though sample is small, number of variables studied is large.

Design can be source of descriptive information to support or invalidate theories.

It has potential to reveal important findings that can generate new hypotheses for testing.

There is no control.

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Correlational Design

Descriptive correlational design Predictive correlational design Model testing design

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Determining Type of Correlational Design

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Descriptive Correlational Design

Describes variables and relationships between variables

There is no attempt to control or manipulate the situation.

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Predictive Correlational Design

Predicts value of one variable based on values obtained for other variables

Independent and dependent variables are defined. Independent variables most effective in prediction are

highly correlated with dependent variables Required development of theory-based mathematical

hypothesis proposing variables expected to effectively predict dependent variable

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Model Testing Design

Tests accuracy of hypothesized causal model (middle-range theory)

All variables are relevant to the model being measured.

A large, heterogeneous sample is required. All paths expressing relationships between

concepts are identified.

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Advantages of Experimental Designs

More controls: design and conduct of study Increased internal validity: decreased threats

to design validity Fewer rival hypotheses

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Essential Elements of Experiments

1. Random assignment of subjects to groups2. Researcher-controlled manipulation of

independent variable3. Researcher control of experimental situation

and setting, including control/comparison group

4. Control of variance• Clearly spelled out sampling criteria• Precisely defined independent variable• Carefully measured dependent variable

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Quasi-experimental Design

Untreated control group design with pretest and posttest

Nonequivalent dependent variables design Removed-treatment design with pretest and

posttest

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Advantages of Quasi-experimental Design

More practical: ease of implementation More feasible: resources, subjects, time,

setting More readily generalized: comparable to

practice

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Study Groups

Groups in comparative descriptive studies Control group Comparison group Equivalent vs. nonequivalent groups

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Randomized Clinical Trial

The design uses large number of subjects to test a treatment’s effect and compare results with a control group who did not receive the treatment.

The subjects come from a reference population.

Randomization of subjects is essential. Usually multiple geographic locations are

used.

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Experimental Interventions

Interventions should result in differences in posttest measures between the treatment and control or comparison groups.

Intervention could be physiological, psychosocial, educational, or a combination.

Nursing is developing a classification system for interventions.

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Critiquing Guidelines for Interventions

Was the experimental intervention described in detail?

Was justification from the literature provided for development of the intervention, and what is the current knowledge?

Was a protocol developed to ensure consistent implementation of the treatment?

Did the study report who implemented the treatment?

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Critiquing Guidelines for Interventions (cont’d)

Was any control group intervention described?

Was an intervention theory provided to explain conclusions?

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Mapping the Design

O = Observation or measurement T = Treatment

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Two-Group Experimental Design

Pretest Treatment Posttest

Experimental group O1 T O2

Control or comparison group

O1 O2

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Quasi-experiment with Several Posttests

Posttests

Pretest Treatment 1 Mo

2 Mo

3 Mo

4 Mo

Experimental group O1 T O2 O3 O4 O5

Control or comparison group

O1 O2 O3 O4 O5

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Replication Research

Replication or repeating a study to confirm original findings

Establishes credibility for the findings Provides support for theory development Encouraged for novice or new researchers

First clinical research project