Limitations of ordinary least squares models in analyzing repeated measures data.
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Creatine supplementation spares muscle glycogen during high intensity intermittent exercise in rats.Early adaptations to six weeks of non-periodized and periodized strength training regimens in recreational malesArtificial neural network modeling using clinical and knowledge independent variables predicts salt intake reduction behavior.Comparison of Nine Statistical Model Based Warfarin Pharmacogenetic Dosing Algorithms Using the Racially Diverse International Warfarin Pharmacogenetic Consortium Cohort Database.Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splinesDoes creatine supplementation improve the plasma lipid profile in healthy male subjects undergoing aerobic training?Training at the optimum power zone produces similar performance improvements to traditional strength trainingGreater eccentric exercise-induced muscle damage by large versus small range of motion with the same end-point.How many days was that? We're still not sure, but we're asking the question better!Identifying Optimal Overload and Taper in Elite Swimmers over TimeBall flight kinematics, release variability and in-season performance in elite baseball pitching.Sensitive radioimmunoassay of total thyroxine (T4) in horses using a simple extraction method.Cerebral Regulation in Different Maximal Aerobic Exercise Modes.The acute effects of varying strength exercises bouts on 5Km running.Improved accuracy of anticoagulant dose prediction using a pharmacogenetic and artificial neural network-based method.Effect of different resistance-training regimens on the WNT-signaling pathway.Resistance training with instability is more effective than resistance training in improving spinal inhibitory mechanisms in Parkinson's disease.Warfarin maintenance dose Prediction for Patients undergoing heart valve replacement- a hybrid model with genetic algorithm and Back-Propagation neural network.
P2860
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P2860
Limitations of ordinary least squares models in analyzing repeated measures data.
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2004 nî lūn-bûn
@nan
2004 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2004 թվականի դեկտեմբերին հրատարակված գիտական հոդված
@hy
2004年の論文
@ja
2004年論文
@yue
2004年論文
@zh-hant
2004年論文
@zh-hk
2004年論文
@zh-mo
2004年論文
@zh-tw
2004年论文
@wuu
name
Limitations of ordinary least squares models in analyzing repeated measures data.
@ast
Limitations of ordinary least squares models in analyzing repeated measures data.
@en
type
label
Limitations of ordinary least squares models in analyzing repeated measures data.
@ast
Limitations of ordinary least squares models in analyzing repeated measures data.
@en
prefLabel
Limitations of ordinary least squares models in analyzing repeated measures data.
@ast
Limitations of ordinary least squares models in analyzing repeated measures data.
@en
P1476
Limitations of ordinary least squares models in analyzing repeated measures data.
@en
P2093
Gilbert W Fellingham
Mark D Ricard
P304
P356
10.1249/01.MSS.0000147580.40591.75
P577
2004-12-01T00:00:00Z