Approximate confidence interval for standard deviation of nonnormal distributions

2006 ◽  
Vol 50 (3) ◽  
pp. 775-782 ◽  
Author(s):  
Douglas G. Bonett
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Nonnormal Distributions ◽  
Approximate Confidence Interval

Using Connectionist Modules for Decision Support

1990 ◽  
Vol 29 (03) ◽  
pp. 167-181 ◽  
Author(s):  
G. Hripcsak
Keyword(s):  
Decision Support ◽  
Standard Deviation ◽  
Confidence Interval ◽  
Posterior Probability ◽  
Back Propagation ◽  
Connectionist Model ◽  
Test Set ◽  
The Third ◽  
Independent Test ◽  
Better Than

AbstractA connectionist model for decision support was constructed out of several back-propagation modules. Manifestations serve as input to the model; they may be real-valued, and the confidence in their measurement may be specified. The model produces as its output the posterior probability of disease. The model was trained on 1,000 cases taken from a simulated underlying population with three conditionally independent manifestations. The first manifestation had a linear relationship between value and posterior probability of disease, the second had a stepped relationship, and the third was normally distributed. An independent test set of 30,000 cases showed that the model was better able to estimate the posterior probability of disease (the standard deviation of residuals was 0.046, with a 95% confidence interval of 0.046-0.047) than a model constructed using logistic regression (with a standard deviation of residuals of 0.062, with a 95% confidence interval of 0.062-0.063). The model fitted the normal and stepped manifestations better than the linear one. It accommodated intermediate levels of confidence well.

Quasi-periodic occurrence of earthquakes in the 1978-1986 Bishop-Mammoth Lakes sequence, eastern California

1987 ◽  
Vol 77 (4) ◽  
pp. 1347-1358
Author(s):  
J. C. Savage ◽  
Robert S. Cockerham
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Convincing Evidence ◽  
Data Selection ◽  
Individual Event ◽  
Physical Explanation ◽  
Interevent Interval ◽  
Prior Event ◽  
Important Activity ◽  
Mammoth Lakes

Abstract In December 1984, Ryall and Hill noted that the five principal events in the Bishop-Mammoth Lakes earthquake sequence occurred at intervals of about 1.5 yr with a standard deviation for an individual event of 0.25 yr. Some data selection was involved in identifying the principal events, although the choices seemed reasonable. The recent Chalfant Valley earthquake (ML = 6.4; 21 July 1986) followed the last prior principal event in the Bishop-Mammoth Lakes sequence by 1.65 yr, and no important activity intervened except one aftershock from the prior event. Thus, the Chalfant Valley earthquake could have been forecast from the observed periodicity. However, the precision of the forecast (±0.8 yr for the 95 per cent confidence interval) is not sufficient to furnish convincing evidence that the Bishop-Mammoth Lakes sequence is quasi-periodic. Extrapolation of the trend established by the six previous events suggests that the next event in the Bishop-Mammoth Lakes sequence would be expected in December 1987 ± 0.7 yr (95 per cent confidence interval). The regularity of the Bishop-Mammoth Lakes sequence is comparable to that of the Parkfield, California, sequence (average interevent interval 20.8 yr with a standard deviation for an individual interval of 6.2 yr). Both sequences consist of six events. There is a plausible physical explanation for the periodicity observed at Parkfield; such an explanation for the Bishop-Mammoth Lakes sequence is lacking.

Translational delivery of Cool Little Kids to prevent child internalising problems: Randomised controlled trial

2017 ◽  
Vol 52 (2) ◽  
pp. 181-191 ◽  
Author(s):  
Jordana K Bayer ◽  
Ruth Beatson ◽  
Lesley Bretherton ◽  
Harriet Hiscock ◽  
Melissa Wake ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Anxiety Disorders ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Controlled Trial ◽  
Secondary Outcomes ◽  
Randomised Controlled ◽  
Internalising Problems

Objective: To determine whether a population-delivered parenting programme assists in preventing internalising problems at school entry for preschool children at-risk with temperamental inhibition. Methods: Design: a randomised controlled trial was used. Setting: the setting was 307 preschool services across eight socioeconomically diverse government areas in Melbourne, Australia. Participants: a total of 545 parents of inhibited 4-year-old children: 498 retained at 1-year follow up. Early intervention: Cool Little Kids parenting group programme was implemented. Primary outcomes: the primary outcomes were child DSM-IV anxiety disorders (assessor blind) and internalising problems. Secondary outcomes: the secondary outcomes were parenting practices and parent mental health. Results: At 1-year follow up (mean (standard deviation) age = 5.8 (0.4) years), there was little difference in anxiety disorders between the intervention and control arms (44.2% vs 50.2%; adjusted odds ratio = 0.86, 95% confidence interval = [0.60, 1.25], p = 0.427). Internalising problems were reduced in the intervention arm (Strengths and Difficulties Questionnaire: abnormal – 24.2% vs 33.0%; adjusted odds ratio = 0.56, 95% confidence interval = [0.35, 0.89], p = 0.014; symptoms – mean (standard deviation) = 2.5 (2.0) vs 2.9 (2.2); adjusted mean difference = –0.47, 95% confidence interval = [–0.81, –0.13], p = 0.006). Parents’ participation in the intervention was modest (29.4% attended most groups, 20.5% used skills most of the time during the year). A priori interaction tests suggested that for children with anxious parents, the intervention reduced anxiety disorders and internalising symptoms after 1 year. Conclusion: Offering Cool Little Kids across the population for inhibited preschoolers does not impact population outcomes after 1 year. Effects may be emerging for inhibited children at highest risk with parent anxiety. Trial outcomes will continue into mid-childhood.

scholarly journals The impact of systolic and diastolic blood pressure variability on mortality is age dependent: Data from the Dublin Outcome Study

2019 ◽  
Vol 27 (4) ◽  
pp. 355-364 ◽  
Author(s):  
Grzegorz Bilo ◽  
Eamon Dolan ◽  
Eoin O'Brien ◽  
Rita Facchetti ◽  
Davide Soranna ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Standard Deviation ◽  
Confidence Interval ◽  
Diastolic Blood Pressure ◽  
Cardiovascular Mortality ◽  
Blood Pressure Variability ◽  
Strong Predictor ◽  
Outcome Study ◽  
Short Term ◽  
The Impact

Background Twenty-four-hour blood pressure variability (BPV) is independently related to cardiovascular outcomes, but limited and conflicting evidence is available on the relative prognostic importance of systolic and diastolic BPV. The aim of this study was to verify the hypothesis that the association of systolic and diastolic blood pressure variability over 24 h with cardiovascular mortality in untreated subjects is affected by age. Design and methods The study included 9154 untreated individuals assessed for hypertension between 1982 and 2002 in the frame of the Dublin Outcome Study, in which 24 h ambulatory blood pressure monitoring was obtained (age 54.1 ± 14.3 years, 47% males). The association of short-term systolic and diastolic blood pressure variability with cardiovascular and all-cause mortality in the entire sample and separately in younger and older age subgroups was assessed over a median follow-up period of 6.3 years. Results Diastolic BPV was directly and independently related to cardiovascular mortality (adjusted hazard ratio (adjHR) for daytime standard deviation 1.16 (95% confidence interval 1.08–1.26)) with no significant differences among age groups. Conversely, systolic BPV was independently associated with cardiovascular mortality only in younger (<50 years) subjects (adjHR for daytime standard deviation 1.72 (95% confidence interval 1.33–2.23)), superseding the predictive value of diastolic BPV in this group. Conclusions Diastolic short-term BPV independently predicts cardiovascular mortality in hypertensive subjects at all ages, while systolic BPV seems a particularly strong predictor in young adults. If confirmed, these findings might improve the understanding of the prognostic value of BPV, with new perspectives for its possible clinical application.

Reliability-Based Design Optimization With Confidence Level Under Input Model Uncertainty

2009 ◽  
Author(s):  
Yoojeong Noh ◽  
K. K. Choi ◽  
Ikjin Lee ◽  
David Gorsich ◽  
David Lamb
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Design Optimization ◽  
Optimum Design ◽  
Upper Bound ◽  
Confidence Level ◽  
Limited Data ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Input Model

For obtaining correct reliability-based optimum design, an input model needs to be accurately estimated in identification of marginal and joint distribution types and quantification of their parameters. However, in most industrial applications, only limited data on input variables is available due to expensive experimental testing costs. The input model generated from the insufficient data might be inaccurate, which will lead to incorrect optimum design. In this paper, reliability-based design optimization (RBDO) with the confidence level is proposed to offset the inaccurate estimation of the input model due to limited data by using an upper bound of confidence interval of the standard deviation. Using the upper bound of the confidence interval of the standard deviation, the confidence level of the input model can be assessed to obtain the confidence level of the output performance, i.e. a desired probability of failure, through the simulation-based design. For RBDO, the estimated input model with the associated confidence level is integrated with the most probable point (MPP)-based dimension reduction method (DRM), which improves accuracy over the first order reliability method (FORM). A mathematical example and a fatigue problem are used to illustrate how the input model with confidence level yields a reliable optimum design by comparing it with the input model obtained using the estimated parameters.

Weighted Simplex Procedures for Determining Boundary Points and Constants for the Univariate and Multivariate Power Methods

2000 ◽  
Vol 25 (4) ◽  
pp. 417-436 ◽  
Author(s):  
Todd C. Headrick ◽  
Shlomo S. Sawilowsky
Keyword(s):  
Standard Deviation ◽  
Lower Bound ◽  
Lagrange Multiplier ◽  
Sufficient Conditions ◽  
Efficient Algorithms ◽  
Data Sets ◽  
Transformation Techniques ◽  
Normal Distributions ◽  
Nonnormal Distributions ◽  
Necessary And Sufficient

The power methods are simple and efficient algorithms used to generate either univariate or multivariate nonnormal distributions with specified values of (marginal) mean, standard deviation, skew, and kurtosis. The power methods are bounded as are other transformation techniques. Given an exogenous value of skew, there is an associated lower bound of kurtosis. Previous approximations of the boundary for the power methods are either incorrect or inadequate. Data sets from education and psychology can be found to lie within, near, or outside tile boundary of the power methods. In view of this, we derived necessary and sufficient conditions using the Lagrange multiplier method to determine the boundary of the power methods. The conditions for locating and classifying modes for distributions on the boundary were also derived. Self-contained interactive Fortran programs using a Weighted Simplex Procedure were employed to generate tabled values of minimum kurtosis for a given value of skew and power constants for various (non)normal distributions.

scholarly journals Hippuric acid in urine: reference values

2002 ◽  
Vol 36 (6) ◽  
pp. 723-727 ◽  
Author(s):  
Maria Elisa PB Siqueira ◽  
Maria José N Paiva
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Reference Values ◽  
Hippuric Acid ◽  
Smoking Habit ◽  
Age Groups ◽  
Reference Value ◽  
Good Health ◽  
Southeastern Brazil ◽  
The Impact

OBJECTIVE: To establish reference values for hippuric acid (HA) excreted in the urine, and to evaluate the impact of age, gender, alcohol, and tobacco, on these levels in a population nonexposed to toluene. METHODS: Reference values for hippuric acid in urine were determined in 115 toluene nonexposed healthy volunteers, from Alfenas city, Southeastern Brazil. A questionnaire was applied to each volunteer and data on occupational and personal habits were collected. Biochemical and hematological analyses were used to confirm the volunteers' good health condition. Reference values were expressed in g HA/g urine creatinine, as mean ± standard deviation (x ± SD), median, 95% confidence interval (95%CI), 95th percentile, and upper reference value (URV, mean +2 SD). RESULTS: Reference values of hippuric acid in urine were: mean ± standard deviation =0.18±0.10; median =0.15; 95% confidence interval =0.16±0.20; 95th percentile = 0.36 and upper reference value (URV, mean +2 SD) =0.38. Statistically significant differences in urinary HA (Wilcoxon - Mann/Whitney, p<0.05) were observed for different genders and age groups. Alcohol ingestion and smoking habit did not significantly affect the results. CONCLUSIONS: The reference values of hippuric acid in urine can be used in biomonitoring programs of workers occupationally exposed to toluene, especially in the southern region of the state of Minas Gerais. Age and gender may affect the HA reference values.

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