Small sample size solutions (Record no. 5170)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02180nam a2200181 a 4500 |
| 001 - CONTROL NUMBER | |
| control field | 37576 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | 0000000000 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240411192359.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200909n s 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 978-0-367-22189-8 |
| 245 10 - TITLE STATEMENT | |
| Title | Small sample size solutions |
| Medium | [electronic resource] : |
| Remainder of title | a guide for applied researchers and practitioners / |
| Statement of responsibility, etc. | [edited by] Rens van de Schoot and Milica Miočevic. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Abingdon, Oxon ; New York, NY : |
| Name of publisher, distributor, etc. | Routledge, |
| Date of publication, distribution, etc. | 2020. |
| 500 ## - GENERAL NOTE | |
| General note | Researchers often have difficulties collecting enough data to test their hypotheses, either because target groups are small or hard to access, or because data collection entails prohibitive costs. Such obstacles may result in data sets that are too small for the complexity of the statistical model needed to answer the research question. This uniquebook provides guidelines and tools for implementing solutions to issues that arise in small sample research. Each chapterillustrates statistical methods that allow researchers to apply the optimal statistical model for their research question when the sample is too small. Thisessential book will enable social and behavioral science researchers to test their hypotheses even when the statistical model required for answering their research question is too complex for the sample sizes they can collect.The statistical models in the book rangefrom the estimation of a population mean to models with latent variables and nested observations, and solutions include both classical and Bayesian methods.All proposed solutions are described in steps researchers can implement with their own data and are accompanied with annotated syntax in R. The methods described in this book will be useful for researchers across the social and behavioral sciences, ranging from medical sciences and epidemiology to psychology, marketing, and economics. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Data sets. |
| Source of heading or term | sears |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Research -- Methodology. |
| Source of heading or term | sears |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://drive.google.com/file/d/1ni38j36Y_MePAwRZUb1Mbxp4et0ljwCt/view?usp=sharing">https://drive.google.com/file/d/1ni38j36Y_MePAwRZUb1Mbxp4et0ljwCt/view?usp=sharing</a> |
| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Main Library | Main Library | E-Resources | 09/09/2020 | 001.42 Sm635 | E001094 | 03/07/2024 | 03/07/2024 | E-Resources |