SAGE Research Methods Foundations最新文献

筛选
英文 中文
Expert Systems 专家系统
SAGE Research Methods Foundations Pub Date : 2004-10-15 DOI: 10.4135/9781526421036842862
J. Ermine
{"title":"Expert Systems","authors":"J. Ermine","doi":"10.4135/9781526421036842862","DOIUrl":"https://doi.org/10.4135/9781526421036842862","url":null,"abstract":"We present a self-adaptive genetic algorithm for the problem of predicting if a Medicare standardized payment to a physical therapist will be above or below the national median. The percentage of Americans 65 and over is expected to increase in the coming years, increasing the need for physical therapy services. As a result, accurate prediction of expected Medicare payments based on local factors will be of increasing importance. A self-adaptive genetic algorithm is an evolutionary algorithm in which some or all of the algorithm’s parameters are evolved over the course of its execution. Self-adaptation is a useful tool both for improving the performance of evolutionary algorithms, as well as improving usability through lessening the amount of parameter tuning required of the algorithm’s user. While other self-adaptive approaches tend to focus on self-adaptation of only a few parameters, our approach self-adapts all of the parameters related to crossover and mutation. We compare the performance of our self-adaptive genetic algorithm with that of logistic regression and a canonical genetic algorithm on the problem of predicting Medicare payments. Logistic regression is a commonly used benchmark for this type of problem and a canonical genetic algorithm is included to allow us to see if any performance costs arise from the self-adaptive mechanisms. Results show that our self-adaptive genetic algorithm is effective at the classification of Medicare standardized payments to physical therapists, achieving accuracies of over 93%. Performance remains strong with training sets as small as 5% of the full data set. The problem representation used by our method allows for the identification of the relevant features for classification which means that our approach is capable of simultaneously performing classification and feature selection.","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114578740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Evidence-Based Practice 循证实践
SAGE Research Methods Foundations Pub Date : 2003-01-15 DOI: 10.4135/9781526421036846490
中村 隆一
{"title":"Evidence-Based Practice","authors":"中村 隆一","doi":"10.4135/9781526421036846490","DOIUrl":"https://doi.org/10.4135/9781526421036846490","url":null,"abstract":"","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133247179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analysis of Proportions 比例分析
SAGE Research Methods Foundations Pub Date : 2002-07-25 DOI: 10.1093/ACPROF:OSO/9780195124408.003.0003
T. Holford
{"title":"Analysis of Proportions","authors":"T. Holford","doi":"10.1093/ACPROF:OSO/9780195124408.003.0003","DOIUrl":"https://doi.org/10.1093/ACPROF:OSO/9780195124408.003.0003","url":null,"abstract":"","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"200 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114005383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Multiple and Generalized Nonparametric Regression 多元和广义非参数回归
SAGE Research Methods Foundations Pub Date : 2000-05-01 DOI: 10.4135/9781412985154
J. Fox
{"title":"Multiple and Generalized Nonparametric Regression","authors":"J. Fox","doi":"10.4135/9781412985154","DOIUrl":"https://doi.org/10.4135/9781412985154","url":null,"abstract":"Local Polynomial Multiple Regression Additive Regression Models Projection-Pursuit Regression Regression Trees Generalized Nonparametric Regression Concluding Remarks Integrating Nonparametric Regression in Statistical Practice","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125361371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 30
Structural Equation Modeling 结构方程建模
SAGE Research Methods Foundations Pub Date : 1998-03-01 DOI: 10.4135/9781526421036883647
G. Marcoulides
{"title":"Structural Equation Modeling","authors":"G. Marcoulides","doi":"10.4135/9781526421036883647","DOIUrl":"https://doi.org/10.4135/9781526421036883647","url":null,"abstract":"The chapters demonstrate two SEM programs with distinct user interfaces and capabilities (Amos and Mplus) with enough specificity that readers can conduct their own analyses without consulting additional resources. Examples from social work literature highlight best practices for the specification, estimation, interpretation, and modification of structural equation models. Oftentimes, confirmatory factor analysis and general structure modeling are the most flexible, powerful, and appropriate choices for social work data.","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128824313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Neural Networks 神经网络
SAGE Research Methods Foundations Pub Date : 1995-06-01 DOI: 10.4135/9781526421036888177
R. Rohwer, M. Wynne-Jones, F. Wysotzki
{"title":"Neural Networks","authors":"R. Rohwer, M. Wynne-Jones, F. Wysotzki","doi":"10.4135/9781526421036888177","DOIUrl":"https://doi.org/10.4135/9781526421036888177","url":null,"abstract":"","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131425829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Causal Analysis With Panel Data 面板数据因果分析
SAGE Research Methods Foundations Pub Date : 1995-01-17 DOI: 10.2307/2291441
S. Finkel
{"title":"Causal Analysis With Panel Data","authors":"S. Finkel","doi":"10.2307/2291441","DOIUrl":"https://doi.org/10.2307/2291441","url":null,"abstract":"Introduction Modeling Change with Panel Data Models with Reciprocal Causation Measurement Error Models Models of Spurious Association Concluding Note on Causal Inference in Panel Analysis","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124075474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 513
Abrahams, Roger 亚伯拉罕,罗杰
SAGE Research Methods Foundations Pub Date : 1900-01-01 DOI: 10.4135/9781526421036821352
{"title":"Abrahams, Roger","authors":"","doi":"10.4135/9781526421036821352","DOIUrl":"https://doi.org/10.4135/9781526421036821352","url":null,"abstract":"","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123069989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Loseke, Donileen
SAGE Research Methods Foundations Pub Date : 1900-01-01 DOI: 10.4135/9781526421036896556
{"title":"Loseke, Donileen","authors":"","doi":"10.4135/9781526421036896556","DOIUrl":"https://doi.org/10.4135/9781526421036896556","url":null,"abstract":"","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116715237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comparative Case Studies 比较个案研究
SAGE Research Methods Foundations Pub Date : 1900-01-01 DOI: 10.4135/9781526421036849021
Nora Carstens, Julia Fleischer, Andree Pruin, Lena Schulze-Gabrechten
{"title":"Comparative Case Studies","authors":"Nora Carstens, Julia Fleischer, Andree Pruin, Lena Schulze-Gabrechten","doi":"10.4135/9781526421036849021","DOIUrl":"https://doi.org/10.4135/9781526421036849021","url":null,"abstract":"","PeriodicalId":243473,"journal":{"name":"SAGE Research Methods Foundations","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126034191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信