Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 19 Process of Quantitative Data Analysis and Interpretation

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Question Tell whether the following statement is true or false: Careful quantitative researchers lay out a data analysis plan as they go along to guide the progress.

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Answer False Careful researchers lay out a data analysis plan in advance to guide that progress.

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Quantitative Data Coded into numerical values Codes developed for legitimate data and missing values Codebook contains decisions about coding and variable naming

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Question What are consistency checks? A.Error-prone processes that requires verification B.Values that lie outside the normal range of values C.Codes that are not legitimate D.Checks for internally consistent information

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Answer D Data entry error proof process that requires verification. Outliers: values that lie outside the normal range of values. Wild codes: codes that are not legitimate. Consistency checks: Checks for internally consistent information.

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Data Entry and Data Cleaning Data entry error proof process that requires verification Data cleaning: –Outliers: values that lie outside the normal range of values –Wild codes: codes that are not legitimate –Consistency checks: checks for internally consistent information

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Missing Data Problems Missing values: –Amount of missing data –How missing data are patterned Critical for intention to treat analysis

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Missing Values Patterns Missing completely at random: occurs when cases with missing values are just a random subsample of all cases in the sample Missing at random: occurs if missingness is related to other variables but not related to the value of the variable that has the missing values Missing not at random: pattern in which the value of the variable that is missing is related to its missingness

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Question Tell whether the following statement is true or false: Listwise deletion is deleting variables with missing values.

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Answer False Listwise deletion: deleting cases with missing values Pairwise deletion: deleting variables with missing values

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Missing Values Strategies Deletion: –Listwise deletion: deleting cases with missing values –Pairwise deletion: deleting variables with missing values Imputation: –Mean substitution: regression based estimation of missing values –Expectation: maximization imputation –Multiple imputation

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Data Transformation Reversing the coding of items Recoding the values of a variable Transforming data to meet statistical assumptions

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Assess Data Quality Evaluating scale reliability Examining distributions for anomalies or extreme outliers that are legitimate values Analyzing the magnitude and direction of any biases

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Peripheral Analysis Determine whether pooling of participants is warranted Tests for cohort effects of ordering effects

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Question Tell whether the following statement is true or false: Table shells are fully laid out tables with numbers in them.

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Answer False Table shells: fully laid out tables without numbers in them

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Formal Analysis Plan Reduce temptation to go on a fishing expedition Table shells: fully laid out tables without numbers in them Supplemental statistical analyses testing competing hypotheses or doing sensitivity analyses can facilitate interpretation

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Interpretation of Quantitative Research Results Credibility of the results Precision of estimates of effects Magnitude of effects Underlying meaning of the results Generalizability of results Implications for future research, theory development, and nursing practice

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Inference Central to interpretation Particulars of study affect inferences that can be made Cautious and skeptical outlook appropriate in drawing conclusion about: –Credibility –Meaning of study results

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Credibility Various approaches Evaluation of the degree of congruence between abstract constructs or idealized methods and proxies actually used Careful assessment of study rigor: –Analysis of validity threats –Various biases that could undermine accuracy of results Corroboration (replication) results through internal or external sources