scholarly journals Applications of statistical experimental designs to improve statistical inference in weed management

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257472
Author(s):  
Steven B. Kim ◽  
Dong Sub Kim ◽  
Christina Magana-Ramirez
Keyword(s):  
Sample Size ◽  
Censored Data ◽  
Dose Response ◽  
Adaptive Design ◽  
Synergetic Effect ◽  
Total Sample ◽  
Experimental Designs ◽  
Right Censored Data ◽  
Balanced Design ◽  
Total Sample Size

In a balanced design, researchers allocate the same number of units across all treatment groups. It has been believed as a rule of thumb among some researchers in agriculture. Sometimes, an unbalanced design outperforms a balanced design. Given a specific parameter of interest, researchers can design an experiment by unevenly distributing experimental units to increase statistical information about the parameter of interest. An additional way of improving an experiment is an adaptive design (e.g., spending the total sample size in multiple steps). It is helpful to have some knowledge about the parameter of interest to design an experiment. In the initial phase of an experiment, a researcher may spend a portion of the total sample size to learn about the parameter of interest. In the later phase, the remaining portion of the sample size can be distributed in order to gain more information about the parameter of interest. Though such ideas have existed in statistical literature, they have not been applied broadly in agricultural studies. In this article, we used simulations to demonstrate the superiority of the experimental designs over the balanced designs under three practical situations: comparing two groups, studying a dose-response relationship with right-censored data, and studying a synergetic effect of two treatments. The simulations showed that an objective-specific design provides smaller error in parameter estimation and higher statistical power in hypothesis testing when compared to a balanced design. We also conducted an adaptive experimental design applied to a dose-response study with right-censored data to quantify the effect of ethanol on weed control. Retrospective simulations supported the benefit of this adaptive design as well. All researchers face different practical situations, and appropriate experimental designs will help utilize available resources efficiently.

scholarly journals Adaptive Design for Staggered-Start Clinical Trial

2016 ◽  
Vol 12 (2) ◽  
Author(s):  
Ao Yuan ◽  
Qizhai Li ◽  
Ming Xiong ◽  
Ming T. Tan
Keyword(s):  
Clinical Trial ◽  
Sample Size ◽  
Adaptive Design ◽  
Optimality Criterion ◽  
Total Sample ◽  
Adaptive Designs ◽  
Initial Sample ◽  
Total Sample Size ◽  
New Type ◽  
Start Trial

AbstractIn phase II and/or III clinical trial study, there are several competing treatments, the goal is to assess the performances of the treatments at the end of the study, the trial design aims to minimize risks to the patients in the trial, according to some given allocation optimality criterion. Recently, a new type of clinical trial, the staggered-start trial has been proposed in some studies, in which different treatments enter the same trial at different times. Some basic questions for this trial are whether optimality can still be kept? under what conditions? and if so how to allocate the the coming patients to treatments to achieve such optimality? Here we propose and study a class of adaptive designs of staggered-start clinical trials, in which for given optimality criterion object, we show that as long as the initial sizes at the beginning of the successive trials are not too large relative to the total sample size, the proposed design can still achieve optimality criterion asymptotically for the allocation proportions as the ordinary trials; if these initial sample sizes have about the same magnitude as the total sample size, full optimality cannot be achieved. The proposed method is simple to use and is illustrated with several examples and a simulation study.

scholarly journals Optimal allocations for two treatment comparisons within the proportional odds cumulative logits model

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250119
Author(s):  
Mirjam Moerbeek
Keyword(s):  
Optimal Design ◽  
Sample Size ◽  
Treatment Effect ◽  
Effect Size ◽  
Total Sample ◽  
Optimal Treatment ◽  
Proportional Odds ◽  
Balanced Design ◽  
Total Sample Size ◽  
Treatment Comparisons

This paper studies optimal treatment allocations for two treatment comparisons when the outcome is ordinal and analyzed by a proportional odds cumulative logits model. The variance of the treatment effect estimator is used as optimality criterion. The optimal design is sought so that this variance is minimal for a given total sample size or a given budget, meaning that the power for the test on treatment effect is maximal, or it is sought so that a required power level is achieved at a minimal total sample size or budget. Results are presented for three, five and seven ordered response categories, three treatment effect sizes and a skewed, bell-shaped or polarized distribution of the response probabilities. The optimal proportion subjects in the intervention condition decreases with the number of response categories and the costs for the intervention relative to those for the control. The relation between the optimal proportion and effect size depends on the distribution of the response probabilities. The widely used balanced design is not always the most efficient; its efficiency as compared to the optimal design decreases with increasing cost ratio. The optimal design is highly robust to misspecification of the response probabilities and treatment effect size. The optimal design methodology is illustrated using two pharmaceutical examples. A Shiny app is available to find the optimal treatment allocation, to evaluate the efficiency of the balanced design and to study the relation between budget or sample size and power.

Farmers Sustainability and Social Justice: Evidences of Land Inequalities in Uttar Pradesh

2020 ◽  
pp. 232-238
Keyword(s):  
Social Justice ◽  
Sample Size ◽  
Field Survey ◽  
Uttar Pradesh ◽  
Total Sample ◽  
Small Farmers ◽  
Land Fragmentation ◽  
Total Sample Size ◽  
Fragmentation Index ◽  
State Economy

The present study is an attempt to inspect the aspect of social justice among the farmers in terms of fragmented land and farmers’ distress in Uttar Pradesh. The data were obtained through field survey via interview scheduled. A sample of 80 respondents from each targeted village namely, Jansar, Sithauli, Charsoni, and Jonai were selected from each region of Uttar Pradesh state economy. Thus, the study used a total sample size of 320 samples. Simmons index (1968) for canvassing the land fragmentation index (LFI) was applied in the Uttar Pradesh context. Further distress was measured via the help of ratios. It flaunted causes and degrees of distress were relatively high among marginal and small farmers. The result of LFI confirms that high fragmentation was a cause of subsistence income among marginal and small farms compared to semi-medium, and medium farms.

Growth in Self-Actualization (Personal Orientation Inventory) in Adult Encounter Groups

1981 ◽  
Vol 1 (1) ◽  
pp. 5-8
Author(s):  
Les Beach
Keyword(s):  
Sample Size ◽  
Personal Growth ◽  
Total Sample ◽  
Small Samples ◽  
Total Sample Size ◽  
Personal Orientation Inventory ◽  
Self Actualization ◽  
Personal Orientation

To test the efficacy of the Personal Orientation Inventory in assessing growth in self-actualization in relation to encounter groups and to provide a more powerful measure of such changes, pre- and posttest data from 3 highly comparable encounter groups (N = 43) were combined for analysis. Results indicated that the Personal Orientation Inventory is a sensitive instrument for assessing personal growth in encounter groups and that a larger total sample size provides more significant results than those reported for small samples (e. g., fewer than 15 participants).

Unequal Randomisation Can Improve the Economic Efficiency of Clinical Trials

1997 ◽  
Vol 2 (2) ◽  
pp. 81-85 ◽  
Author(s):  
David Torgerson ◽  
Marion Campbell
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Statistical Power ◽  
Cost Effective ◽  
Total Sample ◽  
Cost Ratio ◽  
Treatment Groups ◽  
Total Sample Size ◽  
Effectiveness Analysis ◽  
Research Resources

Objectives: In the majority of clinical trials patients are randomised equally between treatment groups. This approach maximises statistical power for a given total sample size. The objectives of this paper were to determine if, when research costs between treatments differ, it is more economically efficient to randomise additional patients to the cheaper treatment, and how the optimum randomisation ratio can be estimated. Methods: Estimation of the most economically efficient randomisation ratio for four hypothetical clinical trials using cost-effectiveness analysis. Results: When research costs differ between treatments, and there is no constraint on total sample size, it is always more cost-effective to randomise more patients to the cheaper treatment. For example, a cost ratio between the lesser and more expensive treatment of ten, results in a randomisation ratio of 3.2:1. Conclusions: Unequal randomisation ratios should be more widely used as this will achieve optimum statistical power for the lowest expenditure of research resources.

scholarly journals Evaluation of the Skin Infections and Conditions among Students of Gomal Medical College Pakistan

2021 ◽  
pp. 218-222
Author(s):  
Shumaila Parveen ◽  
Yaser M. Alahmadi ◽  
Faryal Adnan ◽  
Eshawa Darr ◽  
Ali Alalawi ◽  
...  
Keyword(s):  
Medical Students ◽  
Observational Study ◽  
Sample Size ◽  
Total Sample ◽  
Skin Infections ◽  
Age Group ◽  
Cross Sectional ◽  
Total Sample Size ◽  
Medical College ◽  
Dermatological Disorders

Objective: The objective of the current study is to determine the pattern of dermatological disorders and to find out their connection with different socioeconomically factors among students of the Medical College. Methodology: The Cross sectional observational study was carried out for the period of three months .The research instrument used was the well developed questionnaire. Results: The questionnaire was administered among total 350 students and the most participant age group was the > 22 and that was about 47.4% of the total sample size the more skin complication seen was the acne that was about 59.7%, in addition to this dandruff contributed very heavily to the hair complexities which makes about 35.7% of the sample. Conclusion: Skin infections especially the cosmetic are very common among the Medical students.

scholarly journals TO STUDY THE EFFICACY OF AYURVEDIC TREATMENT IN COVID-19/SARS-COV-2

2021 ◽  
Vol p5 (02) ◽  
pp. 2680-2688
Author(s):  
Ravindrakumar Mane ◽  
Ram Lade
Keyword(s):  
Clinical Trial ◽  
Sample Size ◽  
Death Rate ◽  
Total Sample ◽  
Management Plan ◽  
Effective Management ◽  
Total Sample Size ◽  
Corona Virus ◽  
Ayurvedic Treatment ◽  
Contemporary Medicine

To overcome COVID-19 infection there is no any precise & effective management plan so far available in contemporary Medicine. Therefore, an attempt of administering Ayurvedic medicines to alleviate signs & symptoms of Novel Corona virus is taken into consideration. A clinical trial was performed in hospital with the combination of pure herbo-mineral Ayurvedic medicines named as ‘Shwashara’ along with modern medicines over 93 infected indoor subjects. In total sample size, 76.34% subjects had co-morbidities, after treatment it is been observed that, 29.58% of these subjects did not need oxygen support. 52.69% of sub-jects had HRCT score more than half. 58.06% were recovered within 7 Days. Out of 471 patients, who re-ceived only modern medicines had death rate of 10.02% and the Subjects treated with both systems of medicines have recorded 2.15% death. The ‘Shwashara’ medicine decreases symptoms of pneumonia & COVID-19, strengthen lungs and reduces death rate significantly.

scholarly journals FACTORS AFFECTING STUDENTS’ THESIS COMPLETION ON DEPARTMENT OF MANAGEMENT STIE MIKROSKIL

2021 ◽  
Vol 27 (2) ◽  
Author(s):  
Ella Silvana Ginting ◽  
Apren Halomoan Hutasoit
Keyword(s):  
Sample Size ◽  
Comparative Research ◽  
Total Sample ◽  
Factors Affecting ◽  
Total Sample Size ◽  
Partial Analysis ◽  
Scientific Papers ◽  
Causal Comparative

This study is aimed to investigate the factors that influence the completion of students' final task, thesis. The research is causal comparative research which the data were   obtained by directly surveying respondents through questionnaire. The population in this study were students who finishing their final task, who in semester 8 students students, with total sample size of 67. From the results of the hypothesis analysis simultaneously, a significant value was obtained of 0.000, which means that motivation to graduate on time, the ability to write scientific papers, and the quality of assignment guidance final possess effect on the completion of student final assignments. Partial analysis obtained a significant value of the motivation variable of 0.012, the variable of the ability to write scientific papers of 0.018, and the variable of quality of guidance of 0.000, which means that partially motivation, the ability to write scientific papers, and the quality of final assignment guidance stimulate bring effect on the completion of students' final tasks

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