scholarly journals Another Look at the Logit Transformation of the Survivorship Function

1996 ◽  
Vol 23 (2) ◽  
pp. 147
Author(s):  
S. Mitra
Keyword(s):  
Logit Transformation ◽  
Survivorship Function

scholarly journals Quadriceps activation during maximal isometric and isokinetic contractions: The minimal real difference and its implications

2020 ◽  
pp. 1-13
Author(s):  
Luigi Catino ◽  
Chiara Malloggi ◽  
Stefano Scarano ◽  
Valeria Cerina ◽  
Viviana Rota ◽  
...  
Keyword(s):  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Voluntary Activation ◽  
Real Difference ◽  
Concentric Contractions ◽  
Rehabilitation Programs ◽  
Logit Transformation ◽  
Isokinetic Contractions ◽  
Electrical Stimuli ◽  
Voluntary Contractions

BACKGROUND: A method of measurement of voluntary activation (VA, percent of full muscle recruitment) during isometric and isokinetic concentric contractions of the quadriceps femoris (QF) at 60∘/s and 120∘/s was previously validated. OBJECTIVE: This study aimed to quantify the test-retest minimal real difference (MRD) of VA during isometric (ISOM) and isokinetic concentric contractions of QF (100∘/s, ISOK) in a sample of healthy individuals. METHODS: VA was measured through the interpolated twitch technique. Pairs of electrical stimuli were delivered to the QF at 40∘ of knee flexion during maximal voluntary contractions. Twenty-five healthy participants (20–38 years, 12 women, 13 men) completed two testing sessions with a 14-day interval. VA values were linearized through logit transformation (VAl). The MRD was estimated from intraclass correlation coefficients (model 2.1). RESULTS: The VA (median, range) was 84.20% (38.2–99.9%) in ISOM and 94.22% (33.8-100%) in ISOK. MRD was 0.78 and 1.12 logit for ISOM and ISOK, respectively. As an example, in terms of percent VA these values correspond to a change from 76% to 95% and from 79% to 98% in ISOM and in ISOK, respectively. CONCLUSIONS: The provided MRD values allow to detect significant individual changes in VA, as expected after training and rehabilitation programs.

scholarly journals Network Bandwidth Utilization Prediction Based on Observed SNMP Data

2018 ◽  
Vol 13 (1) ◽  
pp. 160-168
Author(s):  
Nandalal Rana ◽  
Krishna P Bhandari ◽  
Surendra Shrestha
Keyword(s):  
Linear Time ◽  
Arima Model ◽  
Real Data ◽  
Service Planning ◽  
Bandwidth Utilization ◽  
Network Nodes ◽  
Network Bandwidth ◽  
Bandwidth Requirement ◽  
Logit Transformation

 Bandwidth requirement prediction is an important part of network design and service planning. The natural way of predicting bandwidth requirement for existing network is to analyze the past trends and apply appropriate mathematical model to predict for the future. For this research, the historical usage data of FWDR network nodes of Nepal Telecom is subject to univariate linear time series ARIMA model after logit transformation to predict future bandwidth requirement. The predicted data is compared to the real data obtained from the same network and the predicted data has been found to be within 10% MAPE. This model reduces the MAPE by 11.71% and 15.42% respectively as compared to the non-logit transformed ARIMA model at 99% CI. The results imply that the logit transformed ARIMA model has better performance compared to non-logit-transformed ARIMA model. For more accurate and longer term predictions, larger dataset can be taken along with season adjustments and consideration of long term variations.Journal of the Institute of Engineering, 2017, 13(1): 160-168

Test procedure and sample size determination for a proportion study using a double-sampling scheme with two fallible classifiers

2017 ◽  
Vol 28 (4) ◽  
pp. 1019-1043 ◽  
Author(s):  
Shi-Fang Qiu ◽  
Xiao-Song Zeng ◽  
Man-Lai Tang ◽  
Wai-Yin Poon
Keyword(s):  
Sample Size ◽  
Null Hypothesis ◽  
Test Procedure ◽  
Sample Size Determination ◽  
Double Sampling ◽  
Score Statistic ◽  
Wald Statistic ◽  
Test Procedures ◽  
Practical Applications ◽  
Logit Transformation

Double sampling is usually applied to collect necessary information for situations in which an infallible classifier is available for validating a subset of the sample that has already been classified by a fallible classifier. Inference procedures have previously been developed based on the partially validated data obtained by the double-sampling process. However, it could happen in practice that such infallible classifier or gold standard does not exist. In this article, we consider the case in which both classifiers are fallible and propose asymptotic and approximate unconditional test procedures based on six test statistics for a population proportion and five approximate sample size formulas based on the recommended test procedures under two models. Our results suggest that both asymptotic and approximate unconditional procedures based on the score statistic perform satisfactorily for small to large sample sizes and are highly recommended. When sample size is moderate or large, asymptotic procedures based on the Wald statistic with the variance being estimated under the null hypothesis, likelihood rate statistic, log- and logit-transformation statistics based on both models generally perform well and are hence recommended. The approximate unconditional procedures based on the log-transformation statistic under Model I, Wald statistic with the variance being estimated under the null hypothesis, log- and logit-transformation statistics under Model II are recommended when sample size is small. In general, sample size formulae based on the Wald statistic with the variance being estimated under the null hypothesis, likelihood rate statistic and score statistic are recommended in practical applications. The applicability of the proposed methods is illustrated by a real-data example.

scholarly journals Trends in the Quantiles of the Life Table Survivorship Function

2018 ◽  
Vol 34 (5) ◽  
pp. 793-817 ◽  
Author(s):  
Jorge M. Uribe ◽  
Helena Chuliá ◽  
Montserrat Guillen
Keyword(s):  
Life Table ◽  
Survivorship Function

Post-stratification as a tool for enhancing the predictive power of classification methods

2021 ◽  
pp. 125-130
Author(s):  
Francesco D. d'Ovidio ◽  
Angela Maria D'Uggento ◽  
Rossana Mancarella ◽  
Ernesto Toma
Keyword(s):  
Logit Model ◽  
Predictive Power ◽  
Training Sample ◽  
Classification Problems ◽  
Target Variable ◽  
Predictive Capacity ◽  
Logit Transformation ◽  
Segmentation Analysis ◽  
Decision Making Model ◽  
Post Stratification

It is well known that, in classification problems, the predictive capacity of any decision-making model decreases rapidly with increasing asymmetry of the target variable (Sonquist et al., 1973; Fielding 1977). In particular, in segmentation analysis with a categorical target variable, very poor improvements of purity are obtained when the least represented modality counts less than 1/4 of the cases of the most represented modality. The same problem arises with other (theoretically more exhaustive) techniques such as Artificial Neural Networks. Actually, the optimal situation for classification analyses is the maximum uncertainty, that is, equidistribution of the target variable. Some classification techniques are more robust, by using, for example, the less sensitive logit transformation of the target variable (Fabbris & Martini 2002); however, also the logit transformation is strongly affected by the distributive asymmetry of the target variable. In this paper, starting from the results of a direct survey in which the target (binary) variable was extremely asymmetrical (10% vs. 90%, or greater asymmetry), we noted that also the logit model with the most significant parameters had very reduced fitting measures and almost zero predictive power. To solve this predictive issue, we tested post-stratification techniques, artificially symmetrizing a training sample. In this way, a substantially increase of fitting and predictive capacity was achieved, both in the symmetrized sample and, above all, in the original sample. In conclusion of the paper, an application of the same technique to a dataset of very different nature and size is described, demonstrating that the method is stable even in the case of analysis executed with all data of a population.

A Calibrated Combination of Probabilistic Precipitation Forecasts to Achieve a Seamless Transition from Nowcasting to Very Short-Range Forecasting

2020 ◽  
Vol 35 (3) ◽  
pp. 773-791
Author(s):  
Peter Schaumann ◽  
Mathieu de Langlard ◽  
Reinhold Hess ◽  
Paul James ◽  
Volker Schmidt
Keyword(s):  
Real Time ◽  
Short Range ◽  
Lead Times ◽  
New Model ◽  
Combination Model ◽  
Logit Transformation ◽  
Interaction Terms ◽  
Probabilistic Forecasts ◽  
Seamless Transition ◽  
The Ideal

Abstract In this paper, a new model for the combination of two or more probabilistic forecasts is presented. The proposed combination model is based on a logit transformation of the underlying initial forecasts involving interaction terms. The combination aims at approximating the ideal calibration of the forecasts, which is shown to be calibrated, and to maximize the sharpness. The proposed combination model is applied to two precipitation forecasts, Ensemble-MOS and RadVOR, which were developed by Deutscher Wetterdienst. The proposed combination model shows significant improvements in various forecast scores for all considered lead times compared to both initial forecasts. In particular, the proposed combination model is calibrated, even if both initial forecasts are not calibrated. It is demonstrated that the method enables a seamless transition between both initial forecasts across several lead times to be created. Moreover, the method has been designed in such a way that it allows for fast updates in nearly real time.

Does an individual estimation of halflife improve the results of radioiodine therapy of Graves’ disease?

2002 ◽  
Vol 41 (06) ◽  
pp. 240-244 ◽  
Author(s):  
C. Körber ◽  
N. Körber-Hafner ◽  
H. Hänscheid ◽  
Chr. Reiners ◽  
P. Schneider
Keyword(s):  
Radioiodine Therapy ◽  
Dose Calculation ◽  
Multiple Regression Model ◽  
Therapeutic Outcome ◽  
Graves Disease ◽  
Therapeutic Success ◽  
Logit Transformation ◽  
Therapy Success ◽  
The Impact ◽  
Delivered Dose

SummaryAim: The impact of our dosimetry concept on radioiodine therapy success in Graves’ disease (GD) was analysed. Three questions arised: Did individual estimation of pretherapeutic halflife improve therapeutic success?. Did individual dosimetry result in accurate dose calculation?. Did antithyroid medication have a measurable influence on therapeutic success under the prevailing conditions?. Methods: 126 consecutive patients were treated with 200 Gy I-131 in our therapy ward for GD and followed-up six to nine months after therapy. Success quote was assessed using a standardized protocol and treatment was classified as successful when the patient was eu- or hypothyroid, or unsuccessful when he or she presented with a suppressed TSH-level or in hyperthyroid condition after antithyroid medication withdrawel. Antithyroid medication, activity I-131, dose, concentration of fT3 and fT4, specific delivered dose and halflife were put into a multiple regression model to assess their influence on therapeutic success. In order to assess possible factors disturbing the therapeutic outcome, relevant parameters were analyzed using Logit transformation. Results: Out of 126 patients 84 were classified as successfully treated and 42 (33,3%) as failures. A significant influence on the outcome only was found for thyroid mass. However, therapeutic success appeared to be more distinctly determined by the specific delivered dose using an estimated halflife of 5.5 days (Odds: 10.0, p <0.001). Accurate intratherapeutic dosimetry did not play a significant role to enhance therapeutic success. Neither did antihyroid medication during radioiodine therapy exert any significant impact. Conclusions: Measurement of individual intratherapeutic halflife as opposed to an estimate using a standard halflife did not provide improved results concerning the target dose. Retrospectively, the therapeutic outcome on the basis of a measured halflife as compared to a standard halflife did not significantly improve. In addition, no influence of antithyroid medication on therapy success was found.

Assay of Phenobarbital: Adaptation of "EMIT" to the Centrifugal Analyzer

1977 ◽  
Vol 23 (4) ◽  
pp. 738-740 ◽  
Author(s):  
Paul R Finley ◽  
R Jane Williams ◽  
Donald F Lichti ◽  
James M Byers
Keyword(s):  
Liquid Chromatography ◽  
Enzyme Immunoassay ◽  
Gas Liquid Chromatography ◽  
Logit Transformation ◽  
Precision And Accuracy ◽  
Absorbance Data

Abstract We have adapted the centrifugal analyzer to the homo-geneous enzyme immunoassay ("EMIT"®) for phenobar-bital. The assay was modified to give greater range and sensitivity, and less reagent is needed. The transfer disc is prepared with totally automatic pipetting. Results are calculated with a micro-computer that provides a logit transformation of absorbance data. Precision and accuracy are excellent, and results correlate well with those by gas—liquid chromatography.

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