Nursing 503 Session 3 Introduction to Quantitative Research

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Nursing 503 Session 3Introduction to
Quantitative Research

• September 21, 2005

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Contents of presentation

• Research Designs what, why, and characteristics
• Terminology in Research Designs
• Part 1 Characteristics of sound quantitative
  research designs
• Part 2 Validity and Reliability in quantitative
  research

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Research Design How to Decide

• What is the Research Design?
• What is the purpose of research design?
• What are the characteristics of the research
  design?

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Research Designs What Why

• The Research Design
• is a structural framework within which the study
  is planned implemented a blueprint for
  conducting the study.
• Its purpose is to
• Provide the best way to answer the research
  question
• Maximize control over factors which could
  interfere with the desired outcomes
• Instruct the researcher to gather analyze data
  in certain ways, controlling who what are
  studied.

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Types of Research Design

• Descriptive results in description of data
  through words, pictures, charts, tables and
  perhaps statistical described relationships
  (Level I and II research questions)
• Experimental results in inferences based on the
  data which explain the relationship between or
  among variables (Level III)
• Looking for Goodness of Fit

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Characteristics of Research Designs

• The setting for the study laboratory vs. field
• Timing of Data Collection
• Cross-sectional data collected one time only
  from a cross-section of the population at a given
  moment in time
• Longitudinal prospective or the future over a
  period of time to see changes over time
• Historical, retrospective, ex post facto
  looking at events that have occurred in the past

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Continued

• Type Method of Data to be Collected
  Qualitative (interview, focus groups,
  observation) or Quantitative (testing, using
  instruments, measurements)
• Sample Selection, specifically the randomness of
  the sample for the study
• With random sampling every member of the
  population being studied has an equal chance of
  being selected
• Randomness is directly associated with
  generalizability across the entire population

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Key Terms in Research Designs

• VARIABLES
• Independent Variable stands alone, is the cause
  of potential change in cause effect
• Dependent Variable is affected by the
  independent variable(s) is the effect
• Intervening Variable comes between the
  independent and dependent variables, and may
  interfere in some way can also mask the effect
  of the independent variable
• Extraneous Variable are not direct interest in
  the study by could affect the variables measured.

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Other Terms

• Control refers to having control over variables
  which are part of the study as well as those that
  could affect the study
• Allowing for no variation
• Specifying the variation allowed
• Distributing the variation equally across study
• Test for control is Validity External and
  Internal

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Validity in Research Designs

• External Validity
• Is concerned with the extent to which the study
  findings can be generalized beyond the sample
  used in the study
• Degree to which the sample represents the
  population probability sample
• If study is not generalizable based on
  nonprobable sample, then you could be accused of
  making a quantum leap from the data to the
  conclusions.

• Internal Validity
• Extent to which the effects detected in the study
  are a true reflection of reality, rather than the
  result of extraneous variables
• Determined by the way the experimental and
  control groups are formed
• Attributed to the action of the independent
  variable and not something else

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Part 1 Characteristics of sound quantitative
research designs

• OVERVIEW
• Critical elements of a sound quantitative study
• Appropriate sample determining sample size
  adequacy of sample size influence of research
  method
• Factors influencing the power of a statistical
  test

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Critical Elements of a sound quantitative Study

• Quantitative studies are categorized as
  experimental, quasi-experimental or
  non-experimental designs
• Sound Quantitative studies account for
• the intervention and specific testing of the
  effects of the intervention
• Comparisons between or within groups, of rankings
  of the variable, or comparison with other studies
• Controls over independent variable for
  extraneous variables
• Timing of data collection (cross sectional,
  longitudinal)
• Research sites and settings
• Communication with the subjects

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Characteristics of True Quantitative Experiments

• Manipulation The researcher does something to
  some of the subjects (intervention or treatment)
  alters/varies the independent variable to see
  what effect it has on the dependent variable
• Control controls are introduced by the
  researcher over the experimental situation,
  including the use of a control group to be
  compared to a experimental group.
• Randomization the researcher assigns subjects
  to a control or experimental group on a random
  basis

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Gold Standard in Quantitative Research

• Experimental studies
• The randomized trial
• Set out a purpose
• Establish one or more hypotheses to test
  (hypothesis is a prediction of the relationship
  between two or more variables)
• Statistical inference states that the hypothesis
  is framed to indicate no relationship between
  variables this null hypothesis is assumed true
  unless evidence suggests the contrary

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Research Method influencing Sample Size

• Experimental studies, such as clinical trials,
  need large numbers of subjects which are
  randomized
• Need for randomized groups of subjects which
  require larger numbers of subjects to increase
  equity and decrease bias
• Qualitative studies are less inclined to need
  large numbers of subjects, depending on quality
  of technique used or amount of data needed from
  each subject or from entire target group.

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Determining Appropriate Sample

• Sampling Concepts target populations, elements,
  randomization, sample design, sampling frame,
  accessible population, representativeness.
• Sample a subset of elements or members of a
  population employed in such a way as to suggest
  representation from the population from which it
  was drawn.

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How big should the sample be?

• No definitive statistical answer
• Bigger samples have less sampling error
• Smaller samples are easier to manage and are less
  expensive
• The larger the effect size in population the
  smaller the sample needed, and vice versa
• Pilot study can judge the implications of sample
  size for accuracy of final estimates
• Search literature for sampling suggestions in
  similar studies

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Purposes of Literature Review in Quantitative
Research

• Clarify the research project
• Clarify the research problem
• Verify the significance of the research problem
• Specify the purpose of the study
• Identify relevant studies
• Identify relevant theories
• Clarify research subproblems

• Develop definitions of major variables
• Identify limitations and assumptions
• Select a research design
• Identify tools of measurement
• Direct data collection analysis
• Interpret findings

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Sampling error

• The bigger issue for sampling is sample
  distribution and relative error where the sample
  does not reflect the population being studied
  (drawing too many of one kind due to bias or
  small population to draw from, or homogeneity vs.
  heterogeneity of the population)

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A Sampling Distribution

• Distribution patterns
• Sampling Error

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Randomization of Sampling

• Use of a sampling frame (lists or set of elements
  from which sample can be selected)
• Random selection of subjects and placing them
  into groups at random
• Cluster randomization also works where groups of
  individuals can be randomly assigned
  interventions and compared
• Account for systematic bias in groups with
  respect to attributes that could affect dependent
  variable
• Matching of subjects for control and experimental
  groups

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Factors Influencing the Power of a Statistical
Test

• Statistical significance is achieved by
  hypothesis testing null and alternate
• The power of the statistical test is the
  probability of correctly rejecting the null
  hypothesis when it is false, or the ability of
  the test to identify correctly that there is a
  difference between groups in a trial
• Statistical power analysis exploits the
  relationships among four variables sample size
  (N), significance criterion (?),population size
  effect (SE), and statistical power.Each is a
  function of the other three.
• Probability of Type One error In reality null
  hypothesis is true results are significant, but
  null is rejected.

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continued

• Effect size (ES) prespecifying the magnitude of
  the difference between the two groups that can be
  regarded as clinically meaningful and important
  measure of how wrong the null hypothesis is
• Probability (P value) probability of obtaining
  the observed difference between the two groups if
  our null hypothesis is true if the P value for
  the trial lt ?, reject the null hypothesis, vice
  versa

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Part 2 Validity Reliability in Quantitative
Research

• What does validity mean in quantitative research?
• What techniques enhance validity and reliability
  in quantitative research?
• How are validity and reliability evaluated in
  quantitative research?

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Validity in Quantitative Research

• Definition of Validity
• the extent to which any measuring instrument
  measures what it is intended to measure
• Internal and External Validity
• Construct Validity examines the fit between the
  conceptual definitions operational definitions
  of the variables
• Content Validity verifies that the method of
  measurement actually measures the expected
  outcomes.
• Predictive Validity determines the
  effectiveness of the instrument as a predictor of
  a future event
• Statistical Conclusion Validity concerned with
  whether the conclusions about relationships
  and/or differences drawn from statistical
  analysis are an accurate reflection of the real
  world

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Enhancing Validity and Reliability

• Reliability associated with the methods used to
  measure research variables refers to the
  accuracy and consistency of information obtained
  in a study important in interpreting the results
  of statistical analyses and refers to the
  probability that the same results would be
  obtained with different samples
  (generalizability)
• Validity also associated with the methods used
  to measure research variables supports measure
  of generalizability
• Enhance both through vigorous controls of
  research design. including the use of
  manipulation, randomization, and a control group

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Evaluating Validity Reliability

• Instruments used to collect data must be tested
  for accuracy and consistency in measuring what it
  is supposed to measure
• Pilot study to assess instruments, sample, and
  results obtained
• Results obtained from measurement should be true
  results not due to error in instrument.

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Questions Discussion

• Questions??
• Group Answers
• Examples/Experiences