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Guidelines for the application of arima models in time series
Author(s) -
Jensen Louise
Publication year - 1990
Publication title -
research in nursing and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 85
eISSN - 1098-240X
pISSN - 0160-6891
DOI - 10.1002/nur.4770130611
Subject(s) - autoregressive integrated moving average , series (stratigraphy) , time series , computer science , interrupted time series , interrupted time series analysis , management science , psychological intervention , machine learning , medicine , statistics , mathematics , nursing , engineering , paleontology , biology
Time series analysis has been suggested as a valuable approach to evaluating the effectiveness of nursing interventions. Time series analysis techniques provide the tools for analyzing unique behavioral fluctuations through time and a framework for predicting future changes in the individual. Because of its newness, time series modeling has not been used widely in nursing research, but it can provide information about processes in nursing practice. Despite the utility of the interrupted time series design, a number of problems frequently arise in view of the practical and inferential difficulties in conducting interrupted time series research. The inherent limitations of time series analysis procedures are discussed in application to research problems.