Confidence Intervals for Ages of Marsupials Determined from Body Measurements

1981 ◽  
Vol 8 (2) ◽  
pp. 269 ◽  
Author(s):  
JT Wood ◽  
SM Carpenter ◽  
WE Poole
Keyword(s):  
Confidence Interval ◽  
Confidence Intervals ◽  
Growth Curves ◽  
Head Length ◽  
Body Measurements ◽  
Approximate Confidence Intervals ◽  
Using Data

Fitted growth curves for several individual animals for a measurement such as head length will often differ significantly from each other, even though the curves all have the same general form. For construction of a confidence interval for the age of an animal of unknown age with a particular head length, account should be taken of between-animal variation as well as within-animal variation. This paper gives methods for estimating the components of the variation from observations on animals of known age, and for combining them to give approximate confidence intervals for the age of animals of unknown age. The methods are illustrated using data from grey kangaroos.

UNCERTAINTY OF INCREMENTAL COST-EFFECTIVENESS RATIOS

1999 ◽  
Vol 15 (3) ◽  
pp. 608-614 ◽  
Author(s):  
Johan L. Severens ◽  
Theo M. De Boo ◽  
Emmy M. Konst
Keyword(s):  
Cost Effectiveness ◽  
Confidence Interval ◽  
Incremental Cost ◽  
Confidence Intervals ◽  
Incremental Cost Effectiveness Ratio ◽  
Confidence Limits ◽  
Cost Effectiveness Ratio ◽  
Bootstrap Methods ◽  
The Difference ◽  
Using Data

Objective: To compare different methods to estimate the confidence interval of the incremental cost-effectiveness ratio (ICER).Methods: The adequacy of Fieller intervals and three methods for calculating bootstrap intervals are compared based on a simulation of 10,000 trials, using data from one trial.Results: Both Fieller and bootstrap methods lead to unsatisfactory results when the difference in effectiveness is approximately zero. Where this difference is significant, the four methods for calculating confidence intervals for ICER do not give very different results, but Fieller's interval performs best.Conclusions: Since Fieller's confidence limits are relatively easy to compute compared with bootstrap simulations, we recommend using this method.

scholarly journals Assessing the Accuracy of Approximate Confidence Intervals Proposed for the Mean of Poisson Distribution

2020 ◽  
Vol 18 (1) ◽  
pp. 2-13
Author(s):  
Alireza Shirvani ◽  
Malek Fathizadeh
Keyword(s):  
Confidence Interval ◽  
Confidence Intervals ◽  
Poisson Distribution ◽  
Count Data ◽  
Coverage Probability ◽  
Discrete Distribution ◽  
Interval Length ◽  
Average Confidence ◽  
The Mean ◽  
Approximate Confidence Intervals

The Poisson distribution is applied as an appropriate standard model to analyze count data. Because this distribution is known as a discrete distribution, representation of accurate confidence intervals for its distribution mean is extremely difficult. Approximate confidence intervals were presented for the Poisson distribution mean. The purpose of this study is to simultaneously compare several confidence intervals presented, according to the average coverage probability and accurate confidence coefficient and the average confidence interval length criteria.

Approximate Confidence Intervals for Standardized Effect Sizes in the Two-Independent and Two-Dependent Samples Design

2007 ◽  
Vol 32 (1) ◽  
pp. 39-60 ◽  
Author(s):  
Wolfgang Viechtbauer
Keyword(s):  
Monte Carlo ◽  
Confidence Interval ◽  
Confidence Intervals ◽  
Effect Sizes ◽  
Iterative Estimation ◽  
Exact Confidence Intervals ◽  
Standardized Effect Sizes ◽  
Approximate Confidence Intervals ◽  
Exact Confidence Interval ◽  
Dependent Samples

Standardized effect sizes and confidence intervals thereof are extremely useful devices for comparing results across different studies using scales with incommensurable units. However, exact confidence intervals for standardized effect sizes can usually be obtained only via iterative estimation procedures. The present article summarizes several closed-form approximations to the exact confidence interval bounds in the two-independent and two-dependent samples design. Monte Carlo simulations were conducted to determine the accuracy of the various approximations under a wide variety of conditions. All methods except one provided accurate results for moderately large sample sizes and converged to the exact confidence interval bounds as sample size increased.

Empirical Nonparametric Bootstrap Strategies in Quantitative Trait Loci Mapping: Conditioning on the Genetic Model

Genetics ◽  
1998 ◽  
Vol 148 (1) ◽  
pp. 525-535
Author(s):  
Claude M Lebreton ◽  
Peter M Visscher
Keyword(s):  
Quantitative Trait Loci ◽  
Confidence Interval ◽  
Confidence Intervals ◽  
Quantitative Trait ◽  
Genetic Factors ◽  
Genetic Model ◽  
Original Data ◽  
Nonparametric Bootstrap ◽  
Test Protocol ◽  
Trait Loci

AbstractSeveral nonparametric bootstrap methods are tested to obtain better confidence intervals for the quantitative trait loci (QTL) positions, i.e., with minimal width and unbiased coverage probability. Two selective resampling schemes are proposed as a means of conditioning the bootstrap on the number of genetic factors in our model inferred from the original data. The selection is based on criteria related to the estimated number of genetic factors, and only the retained bootstrapped samples will contribute a value to the empirically estimated distribution of the QTL position estimate. These schemes are compared with a nonselective scheme across a range of simple configurations of one QTL on a one-chromosome genome. In particular, the effect of the chromosome length and the relative position of the QTL are examined for a given experimental power, which determines the confidence interval size. With the test protocol used, it appears that the selective resampling schemes are either unbiased or least biased when the QTL is situated near the middle of the chromosome. When the QTL is closer to one end, the likelihood curve of its position along the chromosome becomes truncated, and the nonselective scheme then performs better inasmuch as the percentage of estimated confidence intervals that actually contain the real QTL's position is closer to expectation. The nonselective method, however, produces larger confidence intervals. Hence, we advocate use of the selective methods, regardless of the QTL position along the chromosome (to reduce confidence interval sizes), but we leave the problem open as to how the method should be altered to take into account the bias of the original estimate of the QTL's position.

scholarly journals Quantitative Trait Loci: A Meta-analysis

Genetics ◽  
2000 ◽  
Vol 155 (1) ◽  
pp. 463-473
Author(s):  
Bruno Goffinet ◽  
Sophie Gerber
Keyword(s):  
Quantitative Trait Loci ◽  
Confidence Interval ◽  
Quantitative Trait ◽  
Meta Analysis ◽  
Trait Loci ◽  
Akaike Criterion ◽  
Using Data

Abstract This article presents a method to combine QTL results from different independent analyses. This method provides a modified Akaike criterion that can be used to decide how many QTL are actually represented by the QTL detected in different experiments. This criterion is computed to choose between models with one, two, three, etc., QTL. Simulations are carried out to investigate the quality of the model obtained with this method in various situations. It appears that the method allows the length of the confidence interval of QTL location to be consistently reduced when there are only very few “actual” QTL locations. An application of the method is given using data from the maize database available online at http://www.agron.missouri.edu/.

Identical twins and developmental stability

1962 ◽  
Vol 4 (1) ◽  
pp. 144-164 ◽  
Author(s):  
C. S. Taylor
Keyword(s):  
Growth Curves ◽  
Identical Twins ◽  
Body Measurements ◽  
Frequency Distributions ◽  
Stability Of Development ◽  
Mean Size ◽  
Degree Of Maturity ◽  
The Stability ◽  
Average Size ◽  
Slow Growing

1. The stability with which dairy cattle develop in body size up to 2 years of age was studied in 60 pairs of uniformly treated identical twins, i.e. an assessment was made of the influence of season, genotype, mean size of twin pair, age and degree of maturity on the level of within-pair variability.2. The frequency distributions of size differences shown by one-egg twins were in many cases decidedly leptokurtic.3. The similarity in size of the identical twins studied was only slightly, if at all, influenced by season. Within-pair variability under free outdoor grazing was certainly not any greater than under semi-controlled conditions indoors.4. The stability with which cattle grew appeared to depend on their genotype. Identical twins of the Shorthorn breed were somewhat more alike in size than were the twins of other breed-types; crossbreds were, on average, 50 % less stable than purebreds in average size () ; although crossbreds grew with somewhat greater stability ().5. Whatever their mean size, all pairs of identical twins of the same breed appeared to grow postnatally with more or less equal stability (). Small, slow growing pairs showed a greater disparity in average size ().6. Stability of development continually changed with age but not violently. Each body measurement appeared to have its own characteristic age trend. It is false to believe that variation automatically increases with increasing age. As they grew older, identical twins tended to become less alike in their later maturing body measurements whereas their early maturing body measurements tended to decline in variability. There was an overall trend with degree of maturity; variability steadily increased to a maximum and subsequently declined.7. It is suggested that environmentally induced instability of development may remain at a minimum level so long as growth curves are not seriously distorted from their exponential path to maturity.

A note on growth curves of rabbit lines selected on growth rate or litter size

1993 ◽  
Vol 57 (2) ◽  
pp. 332-334 ◽  
Author(s):  
A. Blasco ◽  
E. Gómez
Keyword(s):  
Growth Rate ◽  
Litter Size ◽  
Growth Curves ◽  
Live Weight ◽  
Maximum Growth ◽  
Maximum Growth Rate ◽  
Standard Errors ◽  
Adult Weight ◽  
Weight Growth ◽  
Using Data

Two synthetic lines of rabbits were used in the experiment. Line V, selected on litter size, and line R, selected on growth rate. Ninety-six animals were randomly collected from 48 litters, taking a male and a female each time. Richards and Gompertz growth curves were fitted. Sexual dimorphism appeared in the line V but not in the R. Values for b and k were similar in all curves. Maximum growth rate took place in weeks 7 to 8. A break due to weaning could be observed in weeks 4 to 5. Although there is a remarkable similarity of the values of all the parameters using data from the first 20 weeks only, the higher standard errors on adult weight would make 30 weeks the preferable time to take data for live-weight growth curves.

Confidence intervals for a difference between lognormal means in cluster randomization trials

2014 ◽  
Vol 26 (2) ◽  
pp. 598-614 ◽  
Author(s):  
Julia Poirier ◽  
GY Zou ◽  
John Koval
Keyword(s):  
Confidence Intervals ◽  
Community Acquired Pneumonia ◽  
Small Sample ◽  
Cluster Randomization ◽  
Critical Pathway ◽  
Arithmetic Means ◽  
Multiple Parameters ◽  
The Difference ◽  
Using Data ◽  
Small Sample Sizes

Cluster randomization trials, in which intact social units are randomized to different interventions, have become popular in the last 25 years. Outcomes from these trials in many cases are positively skewed, following approximately lognormal distributions. When inference is focused on the difference between treatment arm arithmetic means, existent confidence interval procedures either make restricting assumptions or are complex to implement. We approach this problem by assuming log-transformed outcomes from each treatment arm follow a one-way random effects model. The treatment arm means are functions of multiple parameters for which separate confidence intervals are readily available, suggesting that the method of variance estimates recovery may be applied to obtain closed-form confidence intervals. A simulation study showed that this simple approach performs well in small sample sizes in terms of empirical coverage, relatively balanced tail errors, and interval widths as compared to existing methods. The methods are illustrated using data arising from a cluster randomization trial investigating a critical pathway for the treatment of community acquired pneumonia.

Measuring Pump Efficiency: Uncertainty Considerations

2005 ◽  
Vol 127 (4) ◽  
pp. 280-284 ◽  
Author(s):  
Noah D. Manring
Keyword(s):  
Experimental Data ◽  
Confidence Interval ◽  
Confidence Intervals ◽  
Academic Research ◽  
Pump Efficiency ◽  
The Past ◽  
Industrial Sales ◽  
Efficiency Data

The objective of this paper is to analyze the uncertainty associated with pump efficiency measurements and to determine reasonable confidence intervals for these data. In the past, many industrial sales and some pieces of academic research have been based upon the experimental data of pump efficiencies; yet few have questioned the accuracy of the experimental data and no one has provided a confidence interval which reflects the range of uncertainty in the measurement. In this paper, a method for calculating this confidence interval is presented and it is shown that substantially large confidence intervals exist within the testing results of a pump. Furthermore, it is recommended that these confidence intervals be included with the efficiency data whenever it is reported.

Sign in / Sign up

Export Citation Format

Share Document