Journal ArticleDOI
A double bootstrap method to analyze linear models with autoregressive error terms.
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TLDR
A new method for the analysis of linear models that have autoregressive errors is proposed, which is not only relevant in the behavioral sciences for analyzing small-sample time-series intervention models, but is also appropriate for a wide class of small- sample linear model problems.Abstract:
A new method for the analysis of linear models that have autoregressive errors is proposed. The approach is not only relevant in the behavioral sciences for analyzing small-sample time-series intervention models, but it is also appropriate for a wide class of small-sample linear model problems in which there is interest in inferential statements regarding all regression parameters and autoregressive parameters in the model. The methodology includes a double application of bootstrap procedures. The 1st application is used to obtain bias-adjusted estimates of the autoregressive parameters. The 2nd application is used to estimate the standard errors of the parameter estimates. Theoretical and Monte Carlo results are presented to demonstrate asymptotic and small-sample properties of the method; examples that illustrate advantages of the new approach over established time-series methods are described.read more
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Book ChapterDOI
Multigroup Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results
TL;DR: In this article, a comparative analysis of multigroup analysis methods for partial least squares path modeling is presented, and a comparison of the available procedures with which to statistically assess differences between group-specific parameters in PLS path modelling is presented.
Journal ArticleDOI
Conducting Interrupted Time-series Analysis for Single- and Multiple-group Comparisons:
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Characteristics of single-case designs used to assess intervention effects in 2008
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Journal ArticleDOI
Design Specification Issues in Time-Series Intervention Models
TL;DR: In this article, it has been recognized that the two-phase version of the interrupted time-series design can be frequently modeled using a four-parameter design matrix, however, there are differences across writers in the details of the recommended design matrices to be used in the estimation of the four parameters of the model.
Journal ArticleDOI
Making treatment effect inferences from multiple-baseline data: the utility of multilevel modeling approaches.
TL;DR: Interval estimates of the average treatment effect were examined for two specifications of the Level 1 error structure (σ2I and first-order autoregressive) and for five different methods of estimating the degrees of freedom (containment, residual, between—within, Satterthwaite, and Kenward—Roger).
References
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Book
An introduction to the bootstrap
Bradley Efron,Robert Tibshirani +1 more
TL;DR: This article presents bootstrap methods for estimation, using simple arguments, with Minitab macros for implementing these methods, as well as some examples of how these methods could be used for estimation purposes.
Book
Time series analysis, forecasting and control
TL;DR: In this article, a complete revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970 is presented, focusing on practical techniques throughout, rather than a rigorous mathematical treatment of the subject.
Journal ArticleDOI
Time Series Analysis Forecasting and Control
TL;DR: This revision of a classic, seminal, and authoritative book explores the building of stochastic models for time series and their use in important areas of application forecasting, model specification, estimation, and checking, transfer function modeling of dynamic relationships, modeling the effects of intervention events, and process control.
Journal ArticleDOI
Time series analysis, forecasting and control
P. Young,S. Shellswell +1 more
TL;DR: Time series analysis san francisco state university, 6 4 introduction to time series analysis, box and jenkins time seriesAnalysis forecasting and, th15 weeks citation classic eugene garfield, proc arima references 9 3 sas support, time series Analysis forecasting and control pambudi, timeseries analysis forecasting and Control george e.
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