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Nursing Research. PART I І. Lecture №18. Types of Non-probability Sampling. Convenience (Accidental) Sampling Quota Sampling Purposive Sampling Network Sampling Theoretical Sampling. Non-Probability Sampling. Purposive Sampling (Non-Randomized). Theoretical Sampling. Quota.
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Nursing Research PART IІ Lecture №18
Types of Non-probability Sampling • Convenience (Accidental) Sampling • Quota Sampling • Purposive Sampling • Network Sampling • Theoretical Sampling
Non-Probability Sampling Purposive Sampling (Non-Randomized) Theoretical Sampling Quota Convenience Sampling Network
Caution Areas on Data • You see what you look for • You look for what you know • Appropriate statistical strategies for certain types of numbers • If you are a hammer, the world looks like a nail
Dealing With Data (ch. 11) • Developing Data Collection Forms • Planning Data Collection Process • Planning he Organization of Data • Planning Data Analysis • Planning Interpretation & Communication of Findings • Evaluation of the Plan
Data Collection Tasks • Recruiting Subjects • Maintaining Consistency • Maintaining Controls • Protecting Study Integrity • Problem-Solving
Physiological Measures:Reliability and Validity • Accuracy • measurement that has the most precise identifiers for the level of measurement sought • Selectivity • the ability to identify that which is really want to sometimes called specificity • Precision • the amount of reproducibility in measurement • Sensitivity • The amount of a changed parameter that can be detected • Sources of Error
Data Collection Problems • People Problems • Researcher Problems • Institutional Problems • Event Problems • Measurement Validity • Measurement Reliability
Computer Support for Data • Data Input • Data Storage • Data Retrieval • Statistical Analysis
Numbers and Use of Numbers • Nominal (subjective) • A Named category given a number for convenience, e.g. males are 1 and females are 2 • Ordinal (subjective) • A scale that is subjective but shows a direction, e.g. pain scale, cancer staging, all Likert scales • Interval (objective) • Numbers where the interval between them is meaningful, and there is no absolute zero but an arbitrary zero, e. g. a temperature. These numbers can be less than zero. • Ratio (objective) • Numbers where there is an absolute zero which means it is absent or there is a denominator that allows for comparison of meaning and . e. g. number of cases or infections per 100 hospital days, stage 2 skin breakdown per 100 patients.
Bivariate Data AnalysisIndependent Groups • Nominal Data • Chi squared (Two or more samples) • Phi (Two samples) • Cramer’s V (Two samples) • Contingency Coefficient (Two samples) • Lambda (Two samples)
Bivariate Data AnalysisIndependent Groups • Ordinal Data • Mann-Whitney U • Kolmogorov-Smirnov (two-sample test) • Wald-Wolfowitz Run Test • Spearman Rank-Order Correlation • Kendall’s Tau • Kruskal-Wallis One-Way Analysis of Variance by Rank (three or > samples)
Bivariate Data AnalysisIndependent Groups • Interval or Ratio Data • t Test for independent samples • Pearson’s Correlation • Analysis of Variance (Two or more samples) ANOVA • Simple Regression • Multiple Regression Analysis (two or more samples)
Bivariate Data AnalysisDependent Groups • Nominal Data • McNemar Test • Cochran Q Test (three or more samples) • Ordinal Data • Sign Test • Wilcoxon Matched-pairs, Signed-Ranks • Friedman Two-Way Analysis of Variance by Ranks (for three or more samples)
Bivariate Data Analysis Dependent Groups • Interval or Ratio Data • t Test for Related Samples • Analysis of Covariance (for three or more samples) ANCOVA
Multivariate Data Analysis • Interval or Ratio Data • Multiple Regression Analysis • Factorial Analysis of Variance • Analysis of Covariance • Factor Analysis • Discriminate Analysis • Canonical Correlation • Structural Equation Modeling • Time-Series Analysis
Working with Descriptive Data:A Toolkit for Health Care Professionals Using Descriptive Statistics Correlational Descriptive Predictive Descriptive Model Testing Descriptive
Statistics vs. Tools • Inferential Statistic Analysis • Statistics (regression, correlation, t-test, F-test, Multivariate testing etc.) • Descriptive Statistic Analysis • Tools to display information
Critical Path Process (p. 524) • Select the process • Define the process • Form a team • Create the critical path • Make the path a working document
Driving Forces (support efforts) Comparable to Other Schools Recent drop in NCLEX rates Faculty requests Restraining Forces (conflict with efforts) Significant Change in Policy More students would fail DSN had 90-94% NCLEX rates with 72% Force Field Analysis Driving Issues for Moving Minimum Grade at DSN From 72% to 74%
Indicators to be Used in Hospitals • Quantitative measures • Related to one or more dimensions of performance • Help provide data that (when analyzed) give information about quality • Direct attention to potential problems
Types of Indicators • Sentinel-event indicators • Serious injury or death indicator • Aggregate-data indicators • Rating for med errors and patient complaints • Continuous-variable indicators • Number of new bed sores per day • Rate-based indicators • Infections per 1000 patient days
Run Charts • Probably most familiar/used tool • Used to identify trends/patterns in a process over time • Helps track if target level has been attained/maintained
Run Chart – Trend ChartUsed for Self Comparison Quarterly report of new bed sores for Unit X 2008
Comparison Run Charts – Trend Charts-(Dangerous because these are not ratio numbers) Quarterly report of new bed sores for Units A, B, & X for 2008
Histograms • Bar charts that display: • Patterns of variation • The way measurement data are distributed • Snapshot in time • May be more complex to establish; consult statistics textbook if needed
Comparison Run Charts – Trend Charts-(Dangerous because these are not ratio numbers) Quarterly report of new bed sores for Units A, B, & X for 2008
Comparison Run Charts – Trend Charts for Delta Hospital (can be compared equally) Quarterly report of new bed sores per 1000 patient days for Units A, B, & X for 2008.
Control Chart This is the control chart for infections from I.V.s on Unit X With 3 case per 1000 patient days as the standard (std) for 2008. 0.005 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec x x x x x x x x 0.003 x x x x 0.000 Max. Std. Min.
Pie Charts • Descriptive data • Shows a distribution by category • Compared to the Whole
Pie Distribution of new bed sores for hospitalized patients at Delta Hospital Total of 140 new bed sores reported in 2008 36 43 37
Scatter Diagrams • Graphs that show statistical correlation between 2 variables • Used when group wants to: • Test a theory • Analyze raw data • Monitor an action taken
Scatter Diagram Process Min. Program Passing rates in % 76 74 72 NCLEX Scores by % 100%
Surveys Survey’s can carry a risk to them. Also know what Likert Scale you are using and why (1-4, 1-5, 1-10 most common). These are Ordinal Numbers
Naturalistic Inquiry— (Ch. 3) Qualitative Research Methods • Phenomenology • Ethnography • Auto-ethnography • Grounded Theory • Descriptive Qualitative • Historical ?
Non-Probability Sampling Purposive Sampling (Non-Randomized) Theoretical Sampling Quota Convenience Sampling Network
Observational Measurement • Unstructured • Structured • Category Systems • Checklists • Rating Scales • Emic (from within) • Etic (from external view point)
Phenomenology Research:“The Lived Experience” • Phenomenology is a science whose purpose is to describe the appearance of things as a lived experience. • It allows nursing to interpret the nature of consciousness in the world. • It can be descriptive or interpretive (hermeneutic). • It is a philosophy, an method, and an inductive logic strategy
Design Characteristics • Purposive samples of 7-20 usually going for saturation. • Instrument is the researcher • Data collection is by interview of groups or individual that are verbatim, taped, and field notes. • Data collection is directly tied to analysis, that eventually is coded or structured into themes.
Unique Features of Phenomenology • Most of the literature review is conducted at the end of the data collection. It is believed the CF biases the data collection and analysis. • Like Grounded Theory but without a BSP or bias already in mind. • It is conducted by gathering interview data from others. • It is never quantitative, but some would prefer to try and keep it objective.
Five Steps of the Method • Shared Experience is presented • Transform the lived experience into an experience the subject would agree with • Code the data • Put it into written form and create confirmation of the data texts. • Create a complete integration of all of these for a research document • NOTE: In come cases, researchers need to have Bracketing to control an over-riding bias or emotional response
Qualitative Research RigorsThe Five Standards (Ch. 13) • Descriptive Vividness • Methodological Congruence • Theoretical Connectedness • Analytical Preciseness • Heuristic Relevance
Defining Naturalistic RigorStandards 1 and 2 • Descriptive vividness • narratives are texturized, thick, and full of details • the writer shows connections and level of membership • Methodological congruence • details of exactly how the data is gathered with ethical rigor. Does the method match the design?
Defining Naturalistic RigorStandards 3, 4 and 5 • Analytical preciseness • the data is transformed across several levels of abstraction • moving raw data to clusters, interpretations, or theory • Theoretical connectedness • ensuring the theoretical schema is clear and related to the data being collected and a lens for analysis • Heuristic relevance • readers must recognize the phenomenon as applicable, meaningful, & recognizable
Other Types of Rigor Using Trustworthiness • Trustworthy questions • Trustworthy approach • Trustworthy in analysis • Trustworthy and authenticity of data
Ethnography Research Defined as: “Learning from People” By Spradley
Four Types of Ethnography • Classical • Years in the field, constantly observing and making sense of actions. Includes description and behavior. Attempts to describe everything bout the culture. • Systematic • Defines the structure of a culture. • Interpretive (hermeneutic) • To study the culture through inference and analysis looking for “why” behaviors exist. • Critical • Relies on critical theory. Power differentials, who gains and who loses, what supports the status quo.
Historical Roots • Early 1900s had several introductions • Herodotus wrote about travel in Persia • Malinowski’s Study of Trobriand Islanders • Hans Stade wrote about his being in captivity by the wild tribes of Eastern Brazil • The School of Sociology in Chicago, where the city was a laboratory from all the immigrants (dancers, muggers, case studies)
Observation Methods • Emic • From within the research itself as a member or participant of some type. • Etic • From the outside looking in like a camera. It can be a peripheral issue or external observer member.