scholarly journals Assessing the Lognormal Distribution Assumption For the Crude Odds Ratio: Implications For Point and Interval Estimation

2020 ◽  
Author(s):  
David Douglas Newstein
Keyword(s):  
Confidence Intervals ◽  
Standard Method ◽  
Lognormal Distribution ◽  
Odds Ratio ◽  
Estimation Method ◽  
Interval Estimation ◽  
Parametric Bootstrap ◽  
Sampling Distribution ◽  
Estimation Methods ◽  
Crude Odds Ratio

Abstract Background: The assumption that the sampling distribution of the crude Odds Ratio (ORcrude) is a lognormal distribution with parameters mu and sigma leads to the incorrect conclusion that the expectation of the log of ORcrude is equal to the parameter mu. Here, the standard method of point and interval estimation (I) is compared with a modified method utilizing ORstar where ln(ORstar) = ln(ORcrude )– sigma **2/2. Methods: Confidence intervals are obtained utilizing ln(ORstar) by both parametric bootstrap simulations with a percentile derived confidence interval (II), and a simple calculation done by replacing ln(ORcrude) with ln(ORstar) in the standard formula (III) as well as a method proposed by Barendregt (IV), who also noted the bias present in estimating ORtrue by ORcrude. Simulations are conducted for a “protective” exposure (ORtrue < 1) as well as for a “harmful” exposure (ORtrue >1). Results: In simulations the estimation methods (II and III) exhibited the highest level of statistical conclusion validity for their confidence intervals as indicated by one minus the coverage probability being close to alpha. Also, as demonstrated by the MC simulations, these two methods exhibited the least biased point estimates and the narrowest confidence intervals of the four estimation approaches. Conclusions: Monte Carlo simulations prove useful in validating the inferential procedures used in data analysis. In the case of the odds ratio, the standard method of point and interval estimation is based on the assumption that the crude odds ratio has a sampling distribution that is lognormal. Utilizing this assumption, as well as the formula for the expectation of this distribution function, an alternative estimation method was obtained for ORtrue (but different from a method from the earlier report (Barendregt)), that yielded point and interval estimates that MC simulations indicate are the most statistically valid.

scholarly journals Common Medical and Statistical Problems: The Dilemma of the Sample Size Calculation for Sensitivity and Specificity Estimation

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1258
Author(s):  
M. Rosário Oliveira ◽  
Ana Subtil ◽  
Luzia Gonçalves
Keyword(s):  
Sample Size ◽  
Confidence Intervals ◽  
Sensitivity And Specificity ◽  
Sample Size Calculation ◽  
Estimation Method ◽  
Interval Estimation ◽  
Sample Size Determination ◽  
Estimation Methods ◽  
Sample Sizes ◽  
Expected Length

Sample size calculation in biomedical practice is typically based on the problematic Wald method for a binomial proportion, with potentially dangerous consequences. This work highlights the need of incorporating the concept of conditional probability in sample size determination to avoid reduced sample sizes that lead to inadequate confidence intervals. Therefore, new definitions are proposed for coverage probability and expected length of confidence intervals for conditional probabilities, like sensitivity and specificity. The new definitions were used to assess seven confidence interval estimation methods. In order to determine the sample size, two procedures—an optimal one, based on the new definitions, and an approximation—were developed for each estimation method. Our findings confirm the similarity of the approximated sample sizes to the optimal ones. R code is provided to disseminate these methodological advances and translate them into biomedical practice.

scholarly journals Estimating Time: Comparing the Accuracy of Estimation Methods for Interval Timing

2019 ◽  
Author(s):  
Atser Damsma ◽  
Nadine Schlichting ◽  
Hedderik van Rijn ◽  
Warrick Roseboom
Keyword(s):  
Estimation Method ◽  
Interval Estimation ◽  
Reaction Times ◽  
Interval Timing ◽  
Alternative Methods ◽  
Estimation Methods ◽  
Complex Task ◽  
Target Onset ◽  
Spatial Estimation ◽  
Verbal Estimation

In interval timing experiments, motor reproduction is the predominant method used when participants are asked to estimate an interval. However, it is unknown how its accuracy, precision and efficiency compare to alternative methods, such as indicating the duration by spatial estimation on a timeline. In two experiments, we compared different interval estimation methods. In the first experiment, participants were asked to reproduce an interval by means of motor reproduction, timeline estimation, or verbal estimation. We found that, on average, verbal estimates were more accurate and precise than line estimates and motor reproductions. However, we found a bias towards familiar whole second units when giving verbal estimates. Motor reproductions were more precise, but not more accurate than timeline estimates. In the second experiment, we used a more complex task: Participants were presented a stream of digits and one target letters and were subsequently asked to reproduce both the interval to target onset and the duration of the total stream by means of motor reproduction and timeline estimation. We found that motor reproductions were more accurate, but not more precise than timeline estimates. In both experiments, timeline estimates had the lowest reaction times. Overall, our results suggest that the transformation of time into space has only a relatively minor cost. In addition, they show that each estimation method comes with its own advantages, and that the choice of estimation method depends on choices in the experimental design: for example, when using durations with integer durations verbal estimates are superior, yet when testing long durations, motor reproductions are time intensive making timeline estimates a more sensible choice.

scholarly journals Estimating Time: Comparing the Accuracy of Estimation Methods for Interval Timing

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Atser Damsma ◽  
Nadine Schlichting ◽  
Hedderik van Rijn ◽  
Warrick Roseboom
Keyword(s):  
Estimation Method ◽  
Interval Estimation ◽  
Reaction Times ◽  
Interval Timing ◽  
Alternative Methods ◽  
Estimation Methods ◽  
Complex Task ◽  
Target Onset ◽  
Spatial Estimation ◽  
Verbal Estimation

In interval timing experiments, motor reproduction is the predominant method used when participants are asked to estimate an interval. However, it is unknown how its accuracy, precision and efficiency compare to alternative methods, such as indicating the duration by spatial estimation on a timeline. In two experiments, we compared different interval estimation methods. In the first experiment, participants were asked to reproduce an interval by means of motor reproduction, timeline estimation, or verbal estimation. We found that, on average, verbal estimates were more accurate and precise than line estimates and motor reproductions. However, we found a bias towards familiar whole second units when giving verbal estimates. Motor reproductions were more precise, but not more accurate than timeline estimates. In the second experiment, we used a more complex task: Participants were presented a stream of digits and one target letter and were subsequently asked to reproduce both the interval to target onset and the duration of the total stream by means of motor reproduction and timeline estimation. We found that motor reproductions were more accurate, but not more precise than timeline estimates. In both experiments, timeline estimates had the lowest reaction times. Overall, our results suggest that the transformation of time into space has only a relatively minor cost. In addition, they show that each estimation method comes with its own advantages, and that the choice of estimation method depends on choices in the experimental design: for example, when using durations with integer durations verbal estimates are superior, yet when testing long durations, motor reproductions are time intensive making timeline estimates a more sensible choice.

scholarly journals Parametric and semi-parametric bootstrap-based confidence intervals for robust linear mixed models

Methodology ◽  
2021 ◽  
Vol 17 (4) ◽  
pp. 271-295
Author(s):  
Fabio Mason ◽  
Eva Cantoni ◽  
Paolo Ghisletta
Keyword(s):  
Longitudinal Data ◽  
Confidence Intervals ◽  
Robust Estimation ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Parametric Bootstrap ◽  
Estimation Methods ◽  
Low Probability ◽  
Coverage Rates ◽  
Comprehensive Study

The linear mixed model (LMM) is a popular statistical model for the analysis of longitudinal data. However, the robust estimation of and inferential conclusions for the LMM in the presence of outliers (i.e., observations with very low probability of occurrence under Normality) is not part of mainstream longitudinal data analysis. In this work, we compared the coverage rates of confidence intervals (CIs) based on two bootstrap methods, applied to three robust estimation methods. We carried out a simulation experiment to compare CIs under three different conditions: data 1) without contamination, 2) contaminated by within-, or 3) between-participant outliers. Results showed that the semi-parametric bootstrap associated to the composite tau-estimator leads to valid inferential decisions with both uncontaminated and contaminated data. This being the most comprehensive study of CIs applied to robust estimators of the LMM, we provide fully commented R code for all methods applied to a popular example.

scholarly journals The use of the bootstrap method for the assessment of investment effectiveness and risk – the case of confidence intervals estimation for the Sharpe ratio and TailVaR

2020 ◽  
Vol 1/2020 (13) ◽  
pp. 40-50
Author(s):  
Jarno Klaudia ◽  
◽  
Smaga Łukasz ◽  
Keyword(s):  
Confidence Interval ◽  
Confidence Intervals ◽  
Stock Exchange ◽  
Bootstrap Method ◽  
Interval Estimation ◽  
Sharpe Ratio ◽  
Estimation Methods ◽  
Bootstrap Confidence Interval ◽  
Warsaw Stock Exchange ◽  
Confidence Interval Estimation

This paper is aimed at presenting application of bootstrap interval estimation methods to the assessment of financial investment’s effectiveness and risk. At first, we give an overview of various methods of bootstrap confidence interval estimation, i.e. bootstrap-t interval, percentile interval and BCa interval. Then, bootstrap confidence interval estimation methods are used to estimate confidence intervals for the Sharpe ratio and TailVaR of the Warsaw Stock Exchange sectoral indices. The results show that the bootstrap confidence intervals of different types are quite similarly positioned for each of the analysed index and measure. Taking into the account the locations of confidence intervals for both the Sharpe ratio and TailVaR, the real estate sector tends to be the most advantageous from the investor’s viewpoint.

Laboratory Evaluation and Clinical Characteristics of 2,132 Consecutive Unselected Patients with Venous Thromboembolism – Results of the Spanish Multicentric Study on Thrombophilia (EMET*-Study)

1997 ◽  
Vol 77 (03) ◽  
pp. 444-451 ◽  
Author(s):  
José Mateo ◽  
Artur Oliver ◽  
Montserrat Borrell ◽  
Núria Sala ◽  
Jordi Fontcuberta ◽  
...  
Keyword(s):  
Venous Thrombosis ◽  
Odds Ratio ◽  
Protein C ◽  
Protein S ◽  
Laboratory Evaluation ◽  
Clinical Factors ◽  
Recurrent Thrombosis ◽  
Heparin Cofactor Ii ◽  
Crude Odds Ratio ◽  
History Of

SummaryPrevious studies on the prevalence of biological abnormalities causing venous thrombosis and the clinical characteristics of thrombotic patients are conflicting. We conducted a prospective study on 2,132 consecutive evaluable patients with venous thromboembolism to determine the prevalence of biological causes. Antithrombin, protein C, protein S, plasminogen and heparin cofactor-II deficiencies, dysfibrinoge-nemia, lupus anticoagulant and antiphospholipid antibodies were investigated. The risk of any of these alterations in patients with familial, recurrent, spontaneous or juvenile venous thrombosis was assessed. The overall prevalence of protein deficiencies was 12.85% (274/2,132) and antiphospholipid antibodies were found in 4.08% (87/2,132). Ten patients (0.47%) had antithrombin deficiency, 68 (3.19%) protein C deficiency, 155 (7.27%) protein S deficiency, 16 (0.75%) plasminogen deficiency, 8 (0.38%) heparin cofactor-II deficiency and 1 had dysfib-rinogenemia. Combined deficiencies were found in 16 cases (0.75%). A protein deficiency was found in 69 of 303 (22.8%) patients with a family history of thrombosis and in 205/1,829 (11.2%) without a history (crude odds ratio 2.34, 95% Cl 1.72-3.17); in 119/665 (17.9%) patients with thrombosis before the age of 45 and in 153/1,425 (10.7%) after the age of 45 (crude odds ratio 1.81, 95% Cl 1.40-2.35); in 103/616 (16.7%) with spontaneous thrombosis and in 171/1,516 (11.3%) with secondary thrombosis (crude odds ratio 1.58, 95% Cl 1.21-2.06); in 68/358 (19.0%) with recurrent thrombosis and in 206/1,774 (11.6%) with a single episode (crude odds ratio 1.78,95% Cl 1.32-2.41). Patients with combined clinical factors had a higher risk of carrying some deficiency. Biological causes of venous thrombosis can be identified in 16.93% of unselected patients. Family history of thrombosis, juvenile, spontaneous and recurrent thrombosis are the main clinical factors which enhance the risk of a deficiency. Laboratory evaluation of thrombotic patients is advisable, especially if some of these clinical factors are present.

Using The Fully Modified M Method In Estimating The Effect Of Cultivated Area On Barley Production In Iraq For The Period 1970-2018

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Estimation Method ◽  
Estimation Methods ◽  
Autoregressive Moving Average ◽  
Moving Average Models ◽  
Error Terms ◽  
Relationship Of ◽  
The Relationship ◽  
Barley Crop

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.

scholarly journals Comparative Analysis of Kinect-Based and Oculus-Based Gaze Region Estimation Methods in a Driving Simulator

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 26
Author(s):  
David González-Ortega ◽  
Francisco Javier Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez
Keyword(s):  
Virtual Reality ◽  
Comparative Analysis ◽  
Driving Simulator ◽  
Estimation Method ◽  
Estimation Methods ◽  
Gaze Estimation ◽  
Driving Simulators ◽  
Oculus Rift ◽  
Gaze Patterns ◽  
And Performance

Driver’s gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens the scope of research studies as they can relate drivers’ gaze patterns to their features and performance. In this paper, we present two gaze region estimation modules integrated in a driving simulator. One uses the 3D Kinect device and another uses the virtual reality Oculus Rift device. The modules are able to detect the region, out of seven in which the driving scene was divided, where a driver is gazing at in every route processed frame. Four methods were implemented and compared for gaze estimation, which learn the relation between gaze displacement and head movement. Two are simpler and based on points that try to capture this relation and two are based on classifiers such as MLP and SVM. Experiments were carried out with 12 users that drove on the same scenario twice, each one with a different visualization display, first with a big screen and later with Oculus Rift. On the whole, Oculus Rift outperformed Kinect as the best hardware for gaze estimation. The Oculus-based gaze region estimation method with the highest performance achieved an accuracy of 97.94%. The information provided by the Oculus Rift module enriches the driving simulator data and makes it possible a multimodal driving performance analysis apart from the immersion and realism obtained with the virtual reality experience provided by Oculus.

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