scholarly journals Sampling Random Variables: A Paradigm Shift for Opinion Polling

2021 ◽  
Vol 3 (4) ◽  
pp. 439-448
Author(s):  
Gordon G. Bechtel
1986 ◽  
Vol 23 (04) ◽  
pp. 1013-1018
Author(s):  
B. G. Quinn ◽  
H. L. MacGillivray

Sufficient conditions are presented for the limiting normality of sequences of discrete random variables possessing unimodal distributions. The conditions are applied to obtain normal approximations directly for the hypergeometric distribution and the stationary distribution of a special birth-death process.


1985 ◽  
Vol 30 (1) ◽  
pp. 17-17
Author(s):  
Marion Perlmutter
Keyword(s):  

1994 ◽  
Vol 39 (2) ◽  
pp. 197-198
Author(s):  
Raymond T. Garza
Keyword(s):  

2011 ◽  
Author(s):  
Wendy L. Bedwell ◽  
Aaron S. Dietz ◽  
Kathryn E. Keeton ◽  
Daniel Tani ◽  
Gerald Goodwin ◽  
...  
Keyword(s):  

2016 ◽  
Vol 04 (01) ◽  
pp. 4-10

AbstractImmunosuppression permits graft survival after transplantation and consequently a longer and better life. On the other hand, it increases the risk of infection, for instance with cytomegalovirus (CMV). However, the various available immunosuppressive therapies differ in this regard. One of the first clinical trials using de novo everolimus after kidney transplantation [1] already revealed a considerably lower incidence of CMV infection in the everolimus arms than in the mycophenolate mofetil (MMF) arm. This result was repeatedly confirmed in later studies [2–4]. Everolimus is now considered a substance with antiviral properties. This article is based on the expert meeting “Posttransplant CMV infection and the role of immunosuppression”. The expert panel called for a paradigm shift: In a CMV prevention strategy the targeted selection of the immunosuppressive therapy is also a key element. For patients with elevated risk of CMV, mTOR inhibitor-based immunosuppression is advantageous as it is associated with a significantly lower incidence of CMV events.


1985 ◽  
Vol 24 (03) ◽  
pp. 120-130 ◽  
Author(s):  
E. Brunner ◽  
N. Neumann

SummaryThe mathematical basis of Zelen’s suggestion [4] of pre randomizing patients in a clinical trial and then asking them for their consent is investigated. The first problem is to estimate the therapy and selection effects. In the simple prerandomized design (PRD) this is possible without any problems. Similar observations have been made by Anbar [1] and McHugh [3]. However, for the double PRD additional assumptions are needed in order to render therapy and selection effects estimable. The second problem is to determine the distribution of the statistics. It has to be taken into consideration that the sample sizes are random variables in the PRDs. This is why the distribution of the statistics can only be determined asymptotically, even under the assumption of normal distribution. The behaviour of the statistics for small samples is investigated by means of simulations, where the statistics considered in the present paper are compared with the statistics suggested by Ihm [2]. It turns out that the statistics suggested in [2] may lead to anticonservative decisions, whereas the “canonical statistics” suggested by Zelen [4] and considered in the present paper keep the level quite well or may lead to slightly conservative decisions, if there are considerable selection effects.


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