Topic
Secondary data
About: Secondary data is a research topic. Over the lifetime, 523 publications have been published within this topic receiving 12926 citations.
Papers published on a yearly basis
Papers
TL;DR: Issues related to the validity and reliability of measurement instruments used in research are reviewed and key indicators of the quality of a measuring instrument are the reliability and validity of the measures.
Abstract: Purpose. Issues related to the validity and reliability of measurement instruments used in research are reviewed.
Summary. Key indicators of the quality of a measuring instrument are the reliability and validity of the measures. The process of developing and validating an instrument is in large part focused on reducing error in the measurement process. Reliability estimates evaluate the stability of measures, internal consistency of measurement instruments, and interrater reliability of instrument scores. Validity is the extent to which the interpretations of the results of a test are warranted, which depends on the particular use the test is intended to serve. The responsiveness of the measure to change is of interest in many of the applications in health care where improvement in outcomes as a result of treatment is a primary goal of research. Several issues may affect the accuracy of data collected, such as those related to self-report and secondary data sources. Self-report of patients or subjects is required for many of the measurements conducted in health care, but self-reports of behavior are particularly subject to problems with social desirability biases. Data that were originally gathered for a different purpose are often used to answer a research question, which can affect the applicability to the study at hand.
Conclusion. In health care and social science research, many of the variables of interest and outcomes that are important are abstract concepts known as theoretical constructs. Using tests or instruments that are valid and reliable to measure such constructs is a crucial component of research quality.
1,820 citations
Journal Article•
TL;DR: In this paper, a review of the literature demonstrates that schools are frequently called upon to improve by developing high levels of teacher collaboration, and there is a paucity of research investigating the extent to which teachers' collaborative school improvement practices are related to student achievement.
Abstract: Background/Context: A review of the literature demonstrates that schools are frequently called upon to improve by developing high levels of teacher collaboration. At the same time, there is a paucity of research investigating the extent to which teachers’ collaborative school improvement practices are related to student achievement. Purpose: The purpose of this study was to review the literature and empirically test the relationship between a theoretically driven measure of teacher collaboration for school improvement and student achievement. Setting: The data for this study were drawn from students and teachers in a large urban school district located in the midwestern United States. Population: The population for this study came from the elementary schools in one large midwestern school district. Survey data were drawn from a sample of 47 elementary schools with 452 teachers and 2,536 fourth-grade students. Research Design: Hierarchical linear modeling (HLM) was the primary analytic method. Survey data were collected approximately 2 months before students took the mandatory state assessments, which provided the scale scores that served as dependent variables in this research. HLM accounted for the nested nature of the data (students nested in schools). This was a naturalistic study that employed secondary data analysis. There was no intervention, treatment, or randomization. Naturally occurring differences in teachers’ levels of collaboration were measured, and statistical controls for school social context were employed. At the student level, the study employed controls for children’s social and academic backgrounds.
926 citations
28 May 2017
TL;DR: This paper asserts thatsecondary data analysis is a viable method to utilize in the process of inquiry when a systematic procedure is followed and presents an illustrative research application utilizing secondary data analysis in library and information science research.
Abstract: Technological advances have led to vast amounts of data that has been collected, compiled, and archived, and that is now easily accessible for research. As a result, utilizing existing data for research is becoming more prevalent, and therefore secondary data analysis. While secondary analysis is flexible and can be utilized in several ways, it is also an empirical exercise and a systematic method with procedural and evaluative steps, just as in collecting and evaluating primary data. This paper asserts that secondary data analysis is a viable method to utilize in the process of inquiry when a systematic procedure is followed and presents an illustrative research application utilizing secondary data analysis in library and information science research.
787 citations
TL;DR: If the evaluation is satisfactory with respect to the above-mentioned factors relevant to the particular study, the data source could be a very cost-effective way of solving the research problem.
Abstract: Background As part of the development in information technology, increasing amounts of health care data are available for epidemiological research. Methods In this review, we discuss the following factors affecting the value of secondary data in research: 1) completeness of registration of individuals, 2) the accuracy and degree of completeness of the registered data, 3) the size of the data source, 4) the registration period, 5) data accessibility, availability and cost, 6) data format, and 7) possibilities of linkage with other data sources (record linkage). Results and conclusion The importance of these issues depends on the use of the data and on the problems they have to address. If the evaluation is satisfactory with respect to the above-mentioned factors relevant to the particular study, the data source could be a very cost-effective way of solving the research problem.
509 citations
TL;DR: This critical interpretive synthesis examined research articles published between 2006 and 2016 that involved qualitative secondary data analysis and assessed the context, purpose, and methodologies that were reported.
Abstract: While secondary data analysis of quantitative data has become commonplace and encouraged across disciplines, the practice of secondary data analysis with qualitative data has met more criticism and concerns regarding potential methodological and ethical problems. Though commentary about qualitative secondary data analysis has increased, little is known about the current state of qualitative secondary data analysis or how researchers are conducting secondary data analysis with qualitative data. This critical interpretive synthesis examined research articles (n = 71) published between 2006 and 2016 that involved qualitative secondary data analysis and assessed the context, purpose, and methodologies that were reported. Implications of findings are discussed, with particular focus on recommended guidelines and best practices of conducting qualitative secondary data analysis.
430 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 38 |
| 2020 | 40 |
| 2019 | 30 |
| 2018 | 31 |
| 2017 | 43 |
| 2016 | 43 |