1 / 80

Data Collection, Measurement, & Data Quality in Quantitative and Qualitative Research

Data Collection, Measurement, & Data Quality in Quantitative and Qualitative Research. Data Collection Methods. Without appropriate data collection methods, the validity of research conclusions is easily challenged. Data Collection Methods. Using New Data Collect own data for the study.

musson
Download Presentation

Data Collection, Measurement, & Data Quality in Quantitative and Qualitative Research

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. Data Collection, Measurement, & Data Quality in Quantitative and Qualitative Research

  2. Data Collection Methods • Without appropriate data collection methods, the validity of research conclusions is easily challenged

  3. Data Collection Methods • Using New Data • Collect own data for the study

  4. Data Collection Methods • Using Existing Data • Historical research • Use records and other documents from the past • Secondary analysis • Use of data gathered in a previous study

  5. Key Dimensions of Data Collection Methods • Structure • The data collection should be very structured and consistent • Quantifiability • Able to be analyzed statistically • Obtrusiveness • Degree to which people are aware that they are being studied • Objectivity • Try to be as objective as possible

  6. Data Collection Quantitative Research

  7. Types of Data Collection • Self-Reports • Observation • Biophysiologic Measures

  8. Types of Data Collection • Self-Reports • Interviews • Questionnaires • Scales • Vignettes • Projective techniques • Q-sorts

  9. Types of Data Collection: Self-Reports Interviews and Questionnaires (Structured) • Participant's responses to questions by researcher • Data is usually collected by means of a formal, written document (instrument) • Uses an interview schedule for questions that are asked orally (face to face or via phone) • Uses a questionnaire when participants complete the instrument themselves

  10. Types of Data Collection: Self-Reports Interviews and Questionnaires (Structured) • Closed-ended questions (fixed alternative questions) • Response alternatives are specified by the researcher • Ensures comparability of responses • Facilitates analysis • Easy to administer • More efficient time use • Difficult to develop • Could lead to overlooking something important

  11. Types of Data Collection: Self-Reports Interviews and Questionnaires (Structured) • Open-ended questions • Allows participants to respond to questions in their own words • Allows for richer, fuller information

  12. Types of Data Collection: Self-Reports Interviews and Questionnaires (Structured) • Instrument Construction • Develop outline of content of research • Design questions • Pretest • Trial run to determine if instrument is free of biases, errors, etc

  13. Types of Data Collection: Self-Reports • Interviews Vs. Questionnaires • Advantages of questionnaires • Less costly • Require less time and effort to administer • Can be completely anonymous • No biases relating to the researcher being present

  14. Types of Data Collection: Self-Reports • Interviews Vs. Questionnaires • Advantages of Interviews • Response rate is higher in face to face interviews • Effective for those that can not complete questionnaires (children, blind, ESL, elderly) • Questions are less likely to be misinterpreted than questionnaires • Interviews can produce additional information through observation

  15. Types of Data Collection: Self-Reports • Interviews Vs. Questionnaires • Interviews are considered to be superior to questionnaires

  16. Types of Data Collection: Self-Reports Types of Self-Reports (Structured) • Composite Scales (social - psychological) • Vignettes • Projective techniques • Q sorts

  17. Types of Data Collection: Self-Reports Composite Scales (social - psychological) • Scale: assigns a numeric score to people to place them on a continuum with respect to attributes being measured

  18. Types of Data Collection: Self-Reports Composite Scales (social - psychological) • Likert scale • Semantic Differential scale • Visual Analog scale

  19. Types of Data Collection: Self-Reports Composite Scales (social - psychological) • Likert scale (summated rating scales) • Consists of several declarative statements that express a viewpoint • Participant indicates the degree to which they agree to disagree • Able to summate the scores allowing for discrimination among people with different viewpoints

  20. Types of Data Collection: Self-Reports Composite Scales (social - psychological) Example Likert Scale: AU nursing students are very well prepared for working within the current healthcare system Strongly agree Agree Neutral Disagree Strongly disagree

  21. Types of Data Collection: Self-Reports Composite Scales (social - psychological) • Semantic Differential • Participants rate a concept on a series of bipolar adjectives • Can measure any concept • Visual Analog Scale • The scale is a straight line with anchors which are the extreme limits of the experience or feeling • Measures subjective experiences

  22. Types of Data Collection: Self-Reports • Semantic Differential Example AU nursing graduates are: Competent Incompetent Intelligent Dim • Visual Analog Scale Example On a scale of 0 to 10 how would you rate your pain if 10 was the worst pain you have even experienced and 0 was no pain

  23. Advantages of Scales • Scales allow researchers to efficiently quantify the strength and intensities of individual characteristics • Discriminates among people with different attitudes, fears, motives, perceptions, personality traits, needs • Good for group and individual comparisons • Can be implemented either verbally or in writing

  24. Disadvantages of Scales Response set biases • Social Desirability Response Set Bias • Participants give answers that are common social views • Extreme Response Set Bias • Participants express attitudes or feelings in the extreme (always, never) • Acquiescence Response Set Bias • Participants agree with all statements (yea-sayers or nay-sayers)

  25. Disadvantages of Scales • Ways to Reduce Response Set Biases • Counterbalancing: positively and negatively worded statements • Developing sensitively worded questions • Creating a permissive, nonjudgmental atmosphere • Guaranteeing confidentiality

  26. Types of Data Collection: Self-Reports Vignettes • Brief description of events or situations to which participants are asked to react • Information about perceptions, opinions, or knowledge • Questions post vignettes may be open-ended or close-ended • Economical to administer • May contain response biases

  27. Types of Data Collection: Self-Reports Projective Techniques • Verbal self reports to obtain psychological measurements • Seek minimal participants’ conscious cooperation • Ambiguous or unstructured stimuli elicits participants needs, motives, attitudes, personality traits i.e. Inkblot test, word association, role playing, drawing • Useful in children, hearing or speech impaired

  28. Types of Data Collection: Self-Reports Q Sorts • Uses a set of card with words, phrases or statements • Participant sorts cards along a bipolar dimension (agree/disagree)

  29. Advantages of Self-Reporting Methods • Most common method of data collection used by nurses • Reveal information that is difficult to obtain by other means • Can gather retrospective and prospective data • Can measure psychological characteristics

  30. Disadvantages of Self-Reporting Methods • Questionable validity and accuracy • Biases

  31. Types of Data Collection: Observation • Observational Methods • An alternative to self-reports • Can be used to gather information such as characteristics, condition of individuals, verbal communication, nonverbal communication, activities, environmental conditions

  32. Types of Data Collection: Observation Observational Methods • Researcher has flexibility in the following areas: • The focus of observation • What events are to be observed • Concealment • Duration of observation • Method of recording observations

  33. Types of Data Collection: Observation Observational Methods (structured) • Categories and checklists • Rating Scales

  34. Types of Data Collection: Observation Categories and Checklists • Category system: • attempts to designate information in a systematic, quantitative manner • Clear definition of behaviors and characteristics to be observed is necessary • Lists all behaviors or activities the observer wants to observe and records occurrences • Checklist: • instrument to record observations • Rating Scales: • Are tools that require the observer to rate some phenomena along a descriptive continuum

  35. Types of Data Collection: Observation • Observational Sampling • Time sampling • Selection of time periods for observations • Event sampling • Selects behaviors or events for observation

  36. Evaluation of Observational Methods • Advantages • Provides depth and variety of information • Some problems are better suited to observation • Disadvantages • Potential ethical issues • Lack of consent to be observed • Participants reaction to be observed • Biases • Faulty inferences

  37. Types of Data Collection Biophysiologic

  38. Types of Data Collection: Biophysiologic Types of Biophysiologic Measures • In vivo • Measures performed directly within or on living organisms • i.e. blood pressure, temperature • In vitro • Data gathered from participants by extracting some biophysiologic material from them for lab analysis • i.e. blood work, microbiologic measures, cytology and histological measures

  39. Advantages of Biophysiologic Measures • Are relatively accurate and precise • Are objective • Provide valid measures of targeted variables • Equipment is readily available

  40. Disadvantages of Biophysiologic Measures • Measuring tool may affect variables it is attempting to measure • Interferences may create artifact • Energy must often be applied to the organism when taking measurements

  41. Measurement and Assessment of Data

  42. Measurement • Involves rules for assigning numeric values to qualities • Determines how much of an attribute is present • Quantification • Communicates the amount in numbers

  43. Advantages of Measurement • Removes guesswork in gathering information • Tends to be objective • Obtains precise information • Can differentiate among people who possess different degrees of an attribute • Common language

  44. Errors of Measurement • Always the potential for error in all tools • Extraneous factors affect measurement and distort results • Obtained score – is observed score • True score – true score if no errors • Error of measurement – the different between the true and obtained scores

  45. Factors Contributing to Errors of Measurement • Situational contaminants • People’s awareness of observer, environmental factors • Response set biases • Transitory personal factors • Fatigue, mood, hunger (temporary) • Administration variations • Alterations in data collection methods • Item sampling • Errors introduced as a result of sampling

  46. Reliability of Measuring Instruments Reliability • Refers to the consistency with which an instrument measures the attribute • The less variation in repeat measures the higher its reliability

  47. Reliability of Measuring Instruments Reliability • Aspects of reliability • Stability • Internal consistency • Equivalence

  48. Reliability of Measuring Instruments • Stability • The extent to which the same scores are obtained when the instrument is used with the same people on separate occasions • To assess stability: Test-retest reliability • researcher administers the same measure to a sample of people on two occasions and then compares the scores

  49. Reliability of Measuring Instruments • Internal Consistency • Reliable to the extent that all its subparts measure the same characteristic • To assess internal consistency: Split-half technique • the items comprising the test or scale are split into two groups and scored, compute reliability coefficient

  50. Reliability of Measuring Instruments • Equivalence • Determines the consistency or equivalence of the instrument by different observers or raters • To assess equivalence – interrater (interobserver) reliability • Has two or more trained observers make simultaneous, independent observations, compete reliability coefficient

More Related