scholarly journals Dirichlet-multinomial Model with Varying Response Rates over Time

2021 ◽  
Vol 5 (3) ◽  
pp. 413-423
Author(s):  
Jeffrey R. Wilson ◽  
Grace S. C. Chen
1980 ◽  
Vol 17 (1) ◽  
pp. 63-68 ◽  
Author(s):  
Stephen J. Huxley

All mail surveys encounter resistance when they arrive at their destination because they must compete with all other elements in the respondent's environment for his or her time and cooperation. This resistance varies in degree from survey to survey but the pattern of responses it generates over time is remarkably consistent for all surveys: relatively rapid returns in the early stages followed by a gradual tapering off. This pattern can be described by a simple mathematical function, the modified exponential, which relates response rates to elapsed time. The purpose of this article is to indicate how the parameters of this function can be estimated, and how it can be used to predict response speed, forecast the time needed to achieve a desired number of responses, or estimate the number of questionnaires that ought to be mailed out initially.


1977 ◽  
Vol 14 (3) ◽  
pp. 391-395 ◽  
Author(s):  
Michael S. Goodstadt ◽  
Linda Chung ◽  
Reena Kronitz ◽  
Gaynoll Cook

A study involving 2,416 randomly selected magazine readers indicated that response rates to mail questionnaires were significantly increased by the use of 25¢ premiums, but not by the use of a free-book premium or a free-book reward for responding. Response rates over time showed a very significant linear trend with an additional smaller cubic component. A complex significant (cubic) relationship between speed of response and favorability of expressed opinions reinforced conclusions that the broadest spectrum of opinions is obtained best by maximizing response rates.


2020 ◽  
Author(s):  
Alta de Waal ◽  
Daan de Waal

AbstractAccurate prediction of COVID-19 related indicators such as confirmed cases, deaths and recoveries play an important in understanding the spread and impact of the virus, as well as resource planning and allocation. In this study, we approach the prediction problem from a statistical perspective and predict confirmed cases and deaths on a provincial level. We propose the compound Dirichlet Multinomial distribution to estimate the proportion parameter of each province as mutually exclusive outcomes. Furthermore, we make an assumption of exponential growth of the total cummulative counts in order to predict future total counts. The outcomes of this approach is not only prediction. The variation of the proportion parameter is characterised by the Dirichlet distribution, which provides insight in the movement of the pandemic across provinces over time.


2021 ◽  
Vol 1 (1) ◽  
pp. 21-32
Author(s):  
Robert Tortora

This paper reviews response trends over 24 consecutive quarters of a National Random Digit Dial telephone survey. Trends for response rates and refusal rates are studied as well as the components of response rate, namely, contact, cooperation and completion rates. In addition other rates, including answering machine, busy and no answer are studied. While refusal rates declined over the six year period, contact and cooperation rates significantly declined causing response rates to decline. Answering machine rates and busy rates also showed a significant increase over time. Finally, correlation’s among the variables of interest are presented. The response rate is negatively correlated with the busy rate, the answering machine rate and the no answer rate. Implications of the above trends are discussed.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1036.2-1037
Author(s):  
E. Olech ◽  
E. Van Rijen ◽  
F. Hussain ◽  
G. Dennis ◽  
A. Ashrafzadeh ◽  
...  

Background:Randomized controlled trials in Systemic Lupus (SLE) have shown disappointing results for decades. Key challenges may include the heterogenous population coupled with high placebo response rates.Objectives:To evaluate trends in SLE study metrics over time and explore associations between primary endpoint failure and response in placebo/standard of care arms.Methods:Data from Phase II or III trials which enrolled ≥ 100 patients with SLE and reported SRI-4 and/or BICLA responses after a minimum of 24 weeks were included in the analysis. Sample size, recruitment rates, regional patient distributions, and results in placebo arms (at 24-36 weeks or 48-52 weeks) were examined according to the start date of each study in order to determine trends over time. Placebo group SRI-4 response rates in studies that met their primary endpoint were compared with those that did not.Results:Twenty-seven (14 phase II and 13 phase III) studies met the search criteria. Eleven of them met their primary endpoints. The study start dates ranged from Dec 2006 to Jan 2017. Mean/median total subject numbers were 461/349. Mean/median placebo subjects’ age at baseline were 39.9/39.2 and SLEDAI: 10.6/10.6. Mean/median placebo SRI-4 responses at Week 24-36 were 47.2%/45.8% and 42.8%/43% at Week 48-52. For BICLA, the rates were 40.3%/37.2% at Week 24-36 and 33.2%/33.5% at Week 48-52.As expected, lower placebo response was found in trials that met primary endpoints vs studies that did not (p=0.005). Total subject numbers and recruitment rates decreased over time while placebo SRI-4 response rates increased overall (Figure). However, there has been a greater range of placebo responses in more recent trials. Similar trends were observed in BICLA responses at Week 24-36 and 48-52, and in a corticosteroid reduction endpoint (percent of patients with reduction in steroid dose by ≥25% and to ≤7.5 mg/day prednisone/equivalent) at Week 48-52. Enrollment of patients from North America decreased while proportions of Eastern Europeans increased over time (Figure).Conclusion:High placebo response rates pose a continuing challenge in SLE studies and are associated with primary endpoint failures.Clinical trial metrics have been changing over time, with declining size and recruitment rates, possibly due to competition from increasing numbers of studies.These trends should be considered while designing and conducting future trials. Attention to site training and data quality may be particularly important to control high placebo rates, especially as trial sizes decrease.Figure.Disclosure of Interests:Ewa Olech Grant/research support from: BMS, Consultant of: Abbvie, Amgen, Remegen, Employee of: IQVIA, Speakers bureau: Abbvie, Amgen, Merck, Pfizer, UCB, Eduard van Rijen Employee of: IQVIA, Faizi Hussain Employee of: IQVIA, Gregory Dennis Employee of: IQVIA, Ali Ashrafzadeh Employee of: IQVIA, Joan T Merrill Grant/research support from: Xencor, Bristol Myers Squibb, Glaxo Smith Kline, Consultant of: Xencor, Abbvie, UCB, Glaxo Smith Kline, EMD Serono, Astellas, Remegen, Celgene/Bristol Myers Squibb, Exagen, Astra Zeneca, Amgen, Jannsen, Servier, ILTOO, Daitchi Sankyo, Lilly, Paid instructor for: Abbvie, Bristol Myers Squibb


1982 ◽  
Vol 19 (2) ◽  
pp. 261-268 ◽  
Author(s):  
A. Parasuraman

The author discusses some omissions in, and limitations of, recent efforts to model mail survey returns over time. Additional data are analyzed to develop a generalized model of response rate over time, and a practical approach is proposed for estimating mailing requirements for surveys that have specific time deadlines and response requirements.


Author(s):  
Robert F. Schoeni ◽  
Frank Stafford ◽  
Katherine A. Mcgonagle ◽  
Patricia Andreski

It has been well documented that response rates to cross-sectional surveys have declined over the past few decades. It is less clear whether response rates to longitudinal surveys have experienced similar changes over time. This article examines trends in response rates in several major, national longitudinal surveys in the United States and abroad. The authors find that for most of these surveys, the wave-to-wave response rate has not declined. This article also describes the various approaches that these surveys use to minimize attrition.


2019 ◽  
Vol 34 (Supplement_1) ◽  
pp. S98-S102

Abstract Despite the central role of surveys in empirical research, academics have not paid enough attention to the factors that affect response rates. This is especially concerning since survey response rates—of both household and opinion surveys—have been declining over time (Meyer, Mok, and Sullivan, 2015), which might lead to distorted survey results. This paper explores how the underlying design of each survey—such as its length and the day of the week in which the survey was conducted—affects the response rates of the survey.


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