Matthias Schroder

Bio: Matthias Schroder is an academic researcher. The author has contributed to research in topics: Logistic regression & Logistic model tree. The author has an hindex of 1, co-authored 1 publications receiving 934 citations.

Logistic Regression A Self Learning Text

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Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

Abstract: Objectives:Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define C

Analysing Ecological Data

Abstract: Introduction.- Data management and software.- Advice for teachers.- Exploration.- Linear regression.- Generalised linear modelling.- Additive and generalised additive modelling.- Introduction to mixed modelling.- Univariate tree models.- Measures of association.- Ordination--first encounter.- Principal component analysis and redundancy analysis.- Correspondence analysis and canonical correspondence analysis.- Introduction to discriminant analysis.- Principal coordinate analysis and non-metric multidimensional scaling.- Time series analysis--Introduction.- Common trends and sudden changes.- Analysis and modelling lattice data.- Spatially continuous data analysis and modelling.- Univariate methods to analyse abundance of decapod larvae.- Analysing presence and absence data for flatfish distribution in the Tagus estuary, Portugual.- Crop pollination by honeybees in an Argentinean pampas system using additive mixed modelling.- Investigating the effects of rice farming on aquatic birds with mixed modelling.- Classification trees and radar detection of birds for North Sea wind farms.- Fish stock identification through neural network analysis of parasite fauna.- Monitoring for change: using generalised least squares, nonmetric multidimensional scaling, and the Mantel test on western Montana grasslands.- Univariate and multivariate analysis applied on a Dutch sandy beach community.- Multivariate analyses of South-American zoobenthic species--spoilt for choice.- Principal component analysis applied to harbour porpoise fatty acid data.- Multivariate analysis of morphometric turtle data--size and shape.- Redundancy analysis and additive modelling applied on savanna tree data.- Canonical correspondence analysis of lowland pasture vegetation in the humid tropics of Mexico.- Estimating common trends in Portuguese fisheries landings.- Common trends in demersal communities on the Newfoundland-Labrador Shelf.- Sea level change and salt marshes in the Wadden Sea: a time series analysis.- Time series analysis of Hawaiian waterbirds.- Spatial modelling of forest community features in the Volzhsko-Kamsky reserve.

Muscle Weakness and Falls in Older Adults: A Systematic Review and Meta-Analysis

Abstract: Objectives: To evaluate and summarize the evidence of muscle weakness as a risk factor for falls in older adults. Design: Random-effects meta-analysis. Setting: English-language studies indexed in MEDLINE and CINAHL (1985–2002) under the key words aged and accidental falls and risk factors; bibliographies of retrieved papers. Participants: Fifty percent or more subjects in a study were aged 65 and older. Studies of institutionalized and community-dwelling subjects were included. Measurements: Prospective cohort studies that included measurement of muscle strength at inception (in isolation or with other factors) with follow-up for occurrence of falls. Methods: Sample size, population, setting, measure of muscle strength, and length of follow-up, raw data if no risk estimate, odds ratios (ORs), rate ratios, or incidence density ratios. Each study was assessed using the validity criteria: adjustment for confounders, objective definition of fall outcome, reliable method of measuring muscle strength, and blinded outcome measurement. Results: Thirty studies met the selection criteria; data were available from 13. For lower extremity weakness, the combined OR was 1.76 (95% confidence interval (CI)=1.31–2.37) for any fall and 3.06 (95% CI=1.86–5.04) for recurrent falls. For upper extremity weakness the combined OR was 1.53 (95% CI=1.01–2.32) for any fall and 1.41 (95% CI=1.25–1.59) for recurrent falls. Conclusion: Muscle strength (especially lower extremity) should be one of the factors that is assessed and treated in older adults at risk for falls. More clinical trials are needed to isolate whether muscle-strengthening exercises are effective in preventing falls.