Statistics for Spatial Data.

A survey is given of differential expression analyses using the linear modeling features of the limma package. The chapter starts with the simplest replicated designs and progresses through experiments with two or more groups, direct designs, factorial designs and time course experiments. Experiments with technical as well as biological replication are considered. Empirical Bayes test statistics are explained. The use of quality weights, adaptive background correction and control spots in conjunction with linear modelling is illustrated on the β7 data.

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limma: Linear Models for Microarray Data

The aim of this updated guideline is to provide comprehensive and timely evidence-based recommendations on the prevention of future stroke among survivors of ischemic stroke or transient ischemic attack. The guideline is addressed to all clinicians who manage secondary prevention for these patients. Evidence-based recommendations are provided for control of risk factors, intervention for vascular obstruction, antithrombotic therapy for cardioembolism, and antiplatelet therapy for noncardioembolic stroke. Recommendations are also provided for the prevention of recurrent stroke in a variety of specific circumstances, including aortic arch atherosclerosis, arterial dissection, patent foramen ovale, hyperhomocysteinemia, hypercoagulable states, antiphospholipid antibody syndrome, sickle cell disease, cerebral venous sinus thrombosis, and pregnancy. Special sections address use of antithrombotic and anticoagulation therapy after an intracranial hemorrhage and implementation of guidelines.

/pdf/guidelines-for-the-prevention-of-stroke-in-patients-with-4s66xf1dte.pdf

Guidelines for the prevention of stroke in patients with stroke and transient ischemic attack: a guideline for healthcare professionals from the American Heart Association/American Stroke Association

We present here both linear regressions and multivariate analyses correlating three global neuropsychological tests with a number of structural and neurochemical measurements performed on a prospective series of 15 patients with Alzheimer's disease and 9 neuropathologically normal subjects. The statistical data show only weak correlations between psychometric indices and plaques and tangles, but the density of neocortical synapses measured by a new immunocytochemical/densitometric technique reveals very powerful correlations with all three psychological assays. Multivariate analysis by stepwise regression produced a model including midfrontal and inferior parietal synapse density, plus inferior parietal plaque counts with a correlation coefficient of 0.96 for Mattis's Dementia Rating Scale. Plaque density contributed only 26% of that strength.

Physical basis of cognitive alterations in Alzheimer's disease: synapse loss is the major correlate of cognitive impairment.

Mixed linear models were developed by animal breeders to evaluate genetic potential of bulls. Application of mixed models has recently spread to all areas of research, spurred by availability of advanced computer software. Previously, mixed model analyses were implemented by adapting fixed-effect methods to models with random effects. This imposed limitations on applicability because the covariance structure was not modeled. This is the case with PROC GLM in the SAS® System. Recent versions of the SAS System include PROC MIXED. This procedure implements random effects in the statistical model and permits modeling the covariance structure of the data. Thereby, PROC MIXED can compute efficient estimates of fixed effects and valid standard errors of the estimates. Modeling the covariance structure is especially important for analysis of repeated measures data because measurements taken close in time are potentially more highly correlated than those taken far apart in time.

Statistical analysis of repeated measures data using SAS procedures.

Analysis of Messy Data

Background and Purpose—To be useful for clinical research, an outcome measure must be feasible to administer and have sound psychometric attributes, including reliability, validity, and sensitivity to change. This study characterizes the psychometric properties of the Stroke Impact Scale (SIS) Version 2.0. Methods—Version 2.0 of the SIS is a self-report measure that includes 64 items and assesses 8 domains (strength, hand function, ADL/IADL, mobility, communication, emotion, memory and thinking, and participation). Subjects with mild and moderate strokes completed the SIS at 1 month (n=91), at 3 months (n=80), and at 6 months after stroke (n=69). Twenty-five subjects had a replicate administration of the SIS 1 week after the 3-month or 6-month test. We evaluated internal consistency and test-retest reliability. The validity of the SIS domains was examined by comparing the SIS to existing stroke measures and by comparing differences in SIS scores across Rankin scale levels. The mixed model procedure was us...

The Stroke Impact Scale Version 2.0 Evaluation of Reliability, Validity, and Sensitivity to Change

Background and Purpose— Rehabilitation care after stroke is highly variable and increasingly shorter in duration. The effect of therapeutic exercise on impairments and functional limitations after stroke is not clear. The objective of this study was to determine whether a structured, progressive, physiologically based exercise program for subacute stroke produces gains greater than those attributable to spontaneous recovery and usual care. Methods— This randomized, controlled, single-blind clinical trial was conducted in a metropolitan area and 17 participating healthcare institutions. We included persons with stroke who were living in the community. One hundred patients (mean age, 70 years; mean Orpington score, 3.4) consented and were randomized from a screened sample of 582. Ninety-two subjects completed the trial. Intervention was a structured, progressive, physiologically based, therapist-supervised, in-home program of thirty-six 90-minute sessions over 12 weeks targeting flexibility, strength, balan...

Randomized Clinical Trial of Therapeutic Exercise in Subacute Stroke

Analysis of covariance is a very useful but often misunderstood methodology for analyzing data where important characteristics of the experimental units are measured but not included as factors in the design. Analysis of Messy Data, Volume 3: Analysis of Covariance takes the unique approach of treating the analysis of covariance problem by looking

Analysis of Messy Data, Volume III: Analysis of Covariance

The relationships of 6 assays for metmyoglobin (Metmb) reducing ability to color stability and the chemical differences between the inside (ISM) and outside (OSM) beef semimembranosus (SM) muscle after 5 or 14 d storage were investigated. The ISM had less (p Le muscle semimembraneux de boeuf est un muscle large et epais. Cette etude compare les dosages de reduction de la metmyoglobine de la portion interne et externe du muscle et determine leur relation avec les caracteristiques chimiques et la stabilite de la couleur du muscle. La portion interne presente une capacite de reduction inferieure a la portion externe, qui peut etre attribuee partiellement a un taux de consommation d'oxygene et des concentrations en NAD inferieurs.

Dallas E. Johnson

Papers

Analysis of Messy Data

The Stroke Impact Scale Version 2.0 Evaluation of Reliability, Validity, and Sensitivity to Change

Randomized Clinical Trial of Therapeutic Exercise in Subacute Stroke

Analysis of Messy Data, Volume III: Analysis of Covariance

Comparison of Assays for Metmyoglobin Reducing Ability in Beef Inside and Outside Semimembranosus Muscle