scholarly journals ESTIMATION OF PRODUCT OF TWO POPULATION MEANS BY MULTI-AUXILIARY CHARACTERS UNDER DOUBLE SAMPLING THE NON-RESPONDENTS

2019 ◽  
Vol 20 (3) ◽  
pp. 81-95
Author(s):  
B. B. Khare ◽  
R. R. Sinha
Keyword(s):  
Double Sampling ◽  
Population Means

scholarly journals Generalized Classes of Estimators for Population Mean, Ratio and Product Using Rank of Auxiliary Character Under Double Sampling the Non-Respondents

2020 ◽  
Vol 9 (2) ◽  
pp. 1-12
Author(s):  
Raghaw Raman Sinha
Keyword(s):  
Empirical Study ◽  
Comparative Study ◽  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Double Sampling ◽  
Mean Square ◽  
Population Means ◽  
Population Mean ◽  
Auxiliary Character ◽  
Generalized Classes

AbstractIn the present study, generalized classes of estimators for estimating population mean, ratio and product of two population means using rank of auxiliary character in presence of non-response are proposed. The bias and mean square error of proposed classes of estimators are obtained and their performances examined. Specific conditions under which the members of proposed classes of estimators attain minimum mean square error are obtained. Comparative study of the proposed classes of estimators with the relevant estimators is carried out. An empirical study is given to justify the efficiency of the proposed classes of estimators.

The effect of surgery in tenosynovial giant cell tumours as measured by patient-reported outcomes on quality of life and joint function

2019 ◽  
Vol 101-B (3) ◽  
pp. 272-280 ◽  
Author(s):  
F. G. M. Verspoor ◽  
M. J. L. Mastboom ◽  
G. Hannink ◽  
W. T. A. van der Graaf ◽  
M. A. J. van de Sande ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Giant Cell ◽  
Diffuse Type ◽  
Joint Function ◽  
Population Means ◽  
Sf 36 ◽  
Patient Reported ◽  
The Impact

Aims The aim of this study was to evaluate health-related quality of life (HRQoL) and joint function in tenosynovial giant cell tumour (TGCT) patients before and after surgical treatment. Patients and Methods This prospective cohort study run in two Dutch referral centres assessed patient-reported outcome measures (PROMs; 36-Item Short-Form Health Survey (SF-36), visual analogue scale (VAS) for pain, and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)) in 359 consecutive patients with localized- and diffuse-type TGCT of large joints. Patients with recurrent disease (n = 121) and a wait-and-see policy (n = 32) were excluded. Collected data were analyzed at specified time intervals preoperatively (baseline) and/or postoperatively up to five years. Results A total of 206 TGCT patients, 108 localized- and 98 diffuse-type, were analyzed. Median age at diagnosis of localized- and diffuse-type was 41 years (interquartile range (IQR) 29 to 49) and 37 years (IQR 27 to 47), respectively. SF-36 analyses showed statistically significant and clinically relevant deteriorated preoperative and immediate postoperative scores compared with general Dutch population means, depending on subscale and TGCT subtype. After three to six months of follow-up, these scores improved to general population means and continued to be fairly stable over the following years. VAS scores, for both subtypes, showed no statistically significant or clinically relevant differences pre- or postoperatively. In diffuse-type patients, the improvement in median WOMAC score was statistically significant and clinically relevant preoperatively versus six to 24 months postoperatively, and remained up to five years’ follow-up. Conclusion Patients with TGCT report a better HRQoL and joint function after surgery. Pain scores, which vary hugely between patients and in patients over time, did not improve. A disease-specific PROM would help to decipher the impact of TGCT on patients’ daily life and functioning in more detail. Cite this article: Bone Joint J 2019;101-B:272–280.

scholarly journals A semiparametric method for the analysis of outcomes during a gap in HIV care under incomplete outcome ascertainment

2020 ◽  
Vol 12 (s1) ◽  
Author(s):  
Giorgos Bakoyannis ◽  
Lameck Diero ◽  
Ann Mwangi ◽  
Kara K. Wools-Kaloustian ◽  
Constantin T. Yiannoutsos
Keyword(s):  
Electronic Health Record ◽  
East Africa ◽  
Sub Saharan Africa ◽  
Hiv Care ◽  
Double Sampling ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Semiparametric Method ◽  
Program Construction ◽  
Electronic Health

AbstractObjectivesEstimation of the cascade of HIV care is essential for evaluating care and treatment programs, informing policy makers and assessing targets such as 90-90-90. A challenge to estimating the cascade based on electronic health record concerns patients “churning” in and out of care. Correctly estimating this dynamic phenomenon in resource-limited settings, such as those found in sub-Saharan Africa, is challenging because of the significant death under-reporting. An approach to partially recover information on the unobserved deaths is a double-sampling design, where a small subset of individuals with a missed clinic visit is intensively outreached in the community to actively ascertain their vital status. This approach has been adopted in several programs within the East Africa regional IeDEA consortium, the context of our motivating study. The objective of this paper is to propose a semiparametric method for the analysis of competing risks data with incomplete outcome ascertainment.MethodsBased on data from double-sampling designs, we propose a semiparametric inverse probability weighted estimator of key outcomes during a gap in care, which are crucial pieces of the care cascade puzzle.ResultsSimulation studies suggest that the proposed estimators provide valid estimates in settings with incomplete outcome ascertainment under a set of realistic assumptions. These studies also illustrate that a naïve complete-case analysis can provide seriously biased estimates. The methodology is applied to electronic health record data from the East Africa IeDEA Consortium to estimate death and return to care during a gap in care.ConclusionsThe proposed methodology provides a robust approach for valid inferences about return to care and death during a gap in care, in settings with death under-reporting. Ultimately, the resulting estimates will have significant consequences on program construction, resource allocation, policy and decision making at the highest levels.

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