1 / 43

Chapter 8

Chapter 8. Clarifying Quantitative Research Designs. Research Design. Blueprint or detailed plan for conducting a study Purpose, review of literature, and framework provide the basis for the design. Study Purpose. To describe variables To examine relationships To determine differences

Download Presentation

Chapter 8

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Chapter 8 Clarifying Quantitative Research Designs

  2. Research Design Blueprint or detailed plan for conducting a study Purpose, review of literature, and framework provide the basis for the design

  3. 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

  4. 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

  5. Concepts Relevant to Design Causality Multicausality Probability Bias Control Manipulation

  6. 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).

  7. Multicausality There is a cause-and-effect relationship between interrelating variables. There are multiple independent variables causing a change in the dependent variable.

  8. Causality:AB PressureUlcer Multicausality: Years smoking High-fat diet Heart disease Limited exercise Diagram of Causality and Multicausality

  9. 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?

  10. 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.

  11. 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

  12. Control Implemented throughout the design Improved accuracy of findings Increased control in quasi-experimental research Greatest in experimental research

  13. 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

  14. 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

  15. 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?

  16. 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?

  17. 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

  18. 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?

  19. 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?

  20. Types of Quantitative Research Designs Descriptive study designs Correlational study designs Quasi-experimental study designs Experimental study designs

  21. 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

  22. Descriptive Study Designs Typical descriptive design Comparative descriptive design Case study design

  23. Typical Descriptive Design Most commonly used design Examines characteristics of a single sample Identifies phenomenon, variables, conceptual and operational definitions, and describes definitions

  24. 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

  25. 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.

  26. Correlational Design Descriptive correlational design Predictive correlational design Model testing design

  27. Determining Type of Correlational Design

  28. Descriptive Correlational Design Describes variables and relationships between variables There is no attempt to control or manipulate the situation.

  29. 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

  30. 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.

  31. Advantages of Experimental Designs More controls: design and conduct of study Increased internal validity: decreased threats to design validity Fewer rival hypotheses

  32. Essential Elements of Experiments Random assignment of subjects to groups Researcher-controlled manipulation of independent variable Researcher control of experimental situation and setting, including control/comparison group Control of variance Clearly spelled out sampling criteria Precisely defined independent variable Carefully measured dependent variable

  33. Quasi-experimental Design Untreated control group design with pretest and posttest Nonequivalent dependent variables design Removed-treatment design with pretest and posttest

  34. Advantages of Quasi-experimental Design More practical: ease of implementation More feasible: resources, subjects, time, setting More readily generalized: comparable to practice

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

  36. 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.

  37. 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.

  38. 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?

  39. Critiquing Guidelines for Interventions (cont’d) Was any control group intervention described? Was an intervention theory provided to explain conclusions?

  40. Mapping the Design O = Observation or measurement T = Treatment

  41. Two-Group Experimental Design

  42. Quasi-experiment with Several Posttests

  43. 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

More Related