Estimation of a Parameter and Its Exact Confidence Interval Following Sequential Sample Size Reestimation Trials

Biometrics ◽  
2004 ◽  
Vol 60 (4) ◽  
pp. 910-918 ◽  
Author(s):  
Yi Cheng ◽  
Yu Shen
2002 ◽  
Vol 27 (4) ◽  
pp. 335-340 ◽  
Author(s):  
Douglas G. Bonett

An approximate test and confidence interval for coefficient alpha are derived. The approximate test and confidence interval are then used to derive closed-form sample size formulas. The sample size formulas can be used to determine the sample size needed to test coefficient alpha with desired power or to estimate coefficient alpha with desired precision. The sample size formulas closely approximate the sample size requirements for an exact confidence interval or an exact test.


2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Louis M. Houston

We derive a general equation for the probability that a measurement falls within a range of n standard deviations from an estimate of the mean. So, we provide a format that is compatible with a confidence interval centered about the mean that is naturally independent of the sample size. The equation is derived by interpolating theoretical results for extreme sample sizes. The intermediate value of the equation is confirmed with a computational test.


1998 ◽  
Vol 26 (2) ◽  
pp. 57-65 ◽  
Author(s):  
R Kay

If a trial is to be well designed, and the conclusions drawn from it valid, a thorough understanding of the benefits and pitfalls of basic statistical principles is required. When setting up a trial, appropriate sample-size calculation is vital. If initial calculations are inaccurate, trial results will be unreliable. The principle of intent-to-treat in comparative trials is examined. Randomization as a method of selecting patients to treatment is essential to ensure that the treatment groups are equalized in terms of avoiding biased allocation in the mix of patients within groups. Once trial results are available the correct calculation and interpretation of the P-value is important. Its limitations are examined, and the use of the confidence interval to help draw valid conclusions regarding the clinical value of treatments is explored.


2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Helen C Kline ◽  
Zachary D Weller ◽  
Temple Grandin ◽  
Ryan J Algino ◽  
Lily N Edwards-Callaway

Abstract Livestock bruising is both an animal welfare concern and a detriment to the economic value of carcasses. Understanding the causes of bruising is challenging due to the numerous factors that have been shown to be related to bruise prevalence. While most cattle bruising studies collect and analyze data on truckload lots of cattle, this study followed a large number (n = 585) of individual animals from unloading through postmortem processing at five different slaughter plants. Both visual bruise presence and location was recorded postmortem prior to carcass trimming. By linking postmortem data to animal sex, breed, trailer compartment, and traumatic events at unloading, a rich analysis of a number of factors related to bruise prevalence was developed. Results showed varying levels of agreement with other published bruising studies, underscoring the complexity of assessing the factors that affect bruising. Bruising prevalence varied across different sex class types (P < 0.001); 36.5% of steers [95% confidence interval (CI): 31.7, 41.6; n = 378], 52.8% of cows (45.6, 60.0; 193), and 64.3% of bulls (no CI calculated due to sample size; 14) were bruised. There was a difference in bruise prevalence by trailer compartment (P = 0.035) in potbelly trailers, indicating that cattle transported in the top deck were less likely to be bruised (95% CI: 26.6, 40.4; n = 63) compared to cattle that were transported in the bottom deck (95% CI: 39.6, 54.2; n = 89). Results indicated that visual assessment of bruising underestimated carcass bruise trimming. While 42.6% of the carcasses were visibly bruised, 57.9% of carcasses were trimmed due to bruising, suggesting that visual assessment is not able to capture all of the carcass loss associated with bruising. Furthermore, bruises that appeared small visually were often indicators of larger, subsurface bruising, creating an “iceberg effect” of trim loss due to bruising.


1996 ◽  
Vol 14 (9) ◽  
pp. 2546-2551 ◽  
Author(s):  
E Bajetta ◽  
A Di Leo ◽  
L Biganzoli ◽  
L Mariani ◽  
F Cappuzzo ◽  
...  

PURPOSE The aim of the study was to evaluate the activity of vinorelbine (VNLB) in a population of advanced ovarian cancer patients, with particular attention to defining its role in platinum-resistant disease. PATIENTS AND METHODS Thirty-three patients were recruited and treated with VNLB 25 mg/m2 intravenously (IV) weekly. the median age was 53 years, performance status 0 to 2, and number of previous chemotherapy regimens two (range, one to five). Twenty-four patients were platinum-resistant; the remaining nine either were platinum-sensitive (four cases) or had undetermined sensitivity (five cases). RESULTS The mean delivered dose-intensity of VNLB was 67% of the planned level, because 60% of the cycles were delayed due to neutropenia or anemia. Four partial responses (PRs) and one complete response (CR) were observed, for an overall response rate of 15% (95% exact confidence interval, 5.1% to 31.9%). All the responses occurred in the subgroup of 24 platinum-resistant cases, in whom the response rate was 21% (95% exact confidence interval, 7.1% to 42.1%). Seven patients became stabilized on VNLB, and 27% of the cases showed a reduction in serum cancer antigen 125 (CA 125) levels. G3/G4 side effects consisted of neutropenia, anemia, and worsening of preexisting peripheral neuropathy. No treatment-related deaths occurred. CONCLUSION VNLB led to a 21% response rate in the population of heavily pretreated and platinum-resistant ovarian cancer patients. Further studies of VNLB alone or in combination with taxanes are warranted in patients with less pretreatment.


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