Chosen Sample Size Research Articles

Influence of Primary Colors on Memory Retention of Student Gamers

The intricate relationship between colors and memory has been a widespread interest in human psychology. The present study sought to better understand the influence of primary colors on memory retention among student gamers in Higher Education Institutions (HEIs). Applying a quantitative research approach, specifically an experimental research design, examined two independent variables and a control condition. Respondents were composed of 30 student gamers. Most of them were undergraduate students who were exposed to video game experiments and were chosen purposively. In analyzing the collected data, one-way ANOVA and Mauchly’s Test of Sphericity were utilized. Results revealed that primary colors do not significantly influence memory recall. This implies that better memory performance cannot be attributed to the facets of primary colors. Limitations were acknowledged regarding the chosen sample size and the research instruments’ procedural use. Hence, further studies may be conducted by minimizing the confounding variables and other external distractors in the same environment.

Green human resource management and work engagement: Linking HRM performance attributions

Socially responsible companies are adopting sustainability measures to mitigate their impact on the environment. The study investigates the role of green human resource management practices by examining their direct and indirect effect on work engagement. Drawing on the integration of four theories, this research addresses how GHRM practices influence work engagement across various manufacturing industries in North India. This research employed a cluster and purposive sampling approach, selecting districts in Haryana, Delhi, and Rajasthan based on industrial concentration. A judiciously chosen sample size of 362 respondents was deemed optimal, aiming for precision and reliability in exploring GHRM practices among employees and HR managers. Structural equation modeling revealed a significant association between GHRM and work engagement, mediated by managerial support and HRM performance attributions. This study aims to fill the gap in the literature by evaluating the repercussions of GHRM on HRM performance attributions, employing the conservation of resources and attribution theory. The findings contribute valuable insights for organizations aiming to enhance employee engagement and HRM performance attributions through the strategic integration of GHRM.

Leveraging Tacit Knowledge for Teacher Performance in Vocational Schools After-Break

Purpose – The primary objective of this study is to examine the utility of tacit knowledge in enhancing the performance of vocational school teachers who have experienced a career hiatus. Additionally, it seeks to investigate strategies for vocational schools to provide improved support to their teachers in leveraging tacit knowledge to enhance performance, particularly through the promotion of work engagement. Furthermore, the study aims to present a framework for vocational school managers, facilitating the explicit articulation of teachers' tacit knowledge, thereby contributing to the creation and dissemination of new knowledge through effective knowledge management. Design/methodology/approach – In order to gather data for this research, an explanatory survey methodology is employed, with the study's focus directed towards vocational education teachers in the region of West Java. A meticulously chosen sample size of 360 teachers is selected, guided by specific experience criteria and employment within the foundation overseeing the Private vocational school. Structural equation modeling (SEM) serves as the chosen method for hypothesis testing in this study. Findings – This study finds that teacher work engagement serves as a crucial mediator in the relationship between tacit knowledge and performance among vocational school teachers. It is observed that increased tacit knowledge may unexpectedly lead to reduced teacher performance, emphasizing the complexity of this relationship. Tacit knowledge is identified as a valuable resource for addressing workplace demands within vocational education. Moreover, it exerts a significant influence on the motivation process of teachers, subsequently impacting their engagement and overall performance. Interestingly, engagement plays a mitigating role, counteracting the negative effects of suboptimal tacit knowledge utilization by teachers, allowing them to achieve better performance, although not always reaching their full potential based on their rich experiences. Consequently, work engagement emerges as a key mediator, facilitating the translation of tacit knowledge into effective teaching outcomes. These findings shed light on the intricate dynamics of tacit knowledge, engagement, and performance in vocational education, providing valuable insights for educators and policymakers. Originality/value – The originality of this research manifests in its concentrated exploration of the application of tacit knowledge to enhance the performance of vocational school teachers, particularly those who have taken a hiatus in their careers. Additionally, the study introduces a fresh perspective to the realm of vocational education by highlighting the potential outcomes of making teachers' tacit knowledge explicit, with a particular emphasis on work engagement and knowledge management. This novel approach contributes valuable insights to the field, paving the way for further exploration and development.

Sample size determination for external pilot cluster randomised trials with binary feasibility outcomes: a tutorial

Justifying sample size for a pilot trial is a reporting requirement, but few pilot trials report a clear rationale for their chosen sample size. Unlike full-scale trials, pilot trials should not be designed to test effectiveness, and so, conventional sample size justification approaches do not apply. Rather, pilot trials typically specify a range of primary and secondary feasibility objectives. Often, these objectives relate to estimation of parameters that inform the sample size justification for the full-scale trial, many of which are binary. These binary outcomes are referred to as “feasibility outcomes” and include expected prevalence of the primary trial outcome, primary outcome availability, or recruitment or retention proportions.For pilot cluster trials, sample size calculations depend on the number of clusters, the cluster sizes, the anticipated intra-cluster correlation coefficient for the feasibility outcome and the anticipated proportion for that outcome. Of key importance is the intra-cluster correlation coefficient for the feasibility outcome. It has been suggested that correlations for feasibility outcomes are larger than for clinical outcomes measuring effectiveness. Yet, there is a dearth of information on realised values for these correlations.In this tutorial, we demonstrate how to justify sample size in external pilot cluster trials where the objective is to estimate a binary feasibility outcome. We provide sample size calculation formulae for a variety of scenarios, make available an R Shiny app for implementation, and compile a report of intra-cluster correlations for feasibility outcomes from a convenience sample. We demonstrate that unless correlations are very low, external pilot cluster trials can be made more efficient by including more clusters and fewer observations per cluster.

Bayesian design and analysis of two-arm cluster randomized trials using assurance.

We consider the design of a two-arm superiority cluster randomized controlled trial (RCT) with a continuous outcome. We detail Bayesian inference for the analysis of the trial using a linear mixed-effects model. The treatment is compared to control using the posterior distribution for the treatment effect. We develop the form of the assurance to choose the sample size based on this analysis, and its evaluation using a two loop Monte Carlo sampling scheme. We assess the proposed approach, considering the effect of different forms of prior distribution, and the number of Monte Carlo samples needed in both loops for accurate determination of the assurance and sample size. Based on this assessment, we provide general advice on each of these choices. We apply the approach to the choice of sample size for a cluster RCT into poststroke incontinence, and compare the resulting sample size to that from assurance based on a Wald test for the treatment effect. The Bayesian approach to design and analysis developed in this article can offer advantages in terms of an increase in the robustness of the chosen sample size to parameter mis-specification and reduced sample sizes if prior information indicates the treatment effect is likely to be larger than the minimal clinically important difference.

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In today’s dynamic and competitive business environment, solvency is a critical success factor that strategically enables a firm to structure their resources in meeting their financial obligations on the short, medium and long-term bases. However, the inability of a firm to maintain acceptable level of financial stability threatens its future growth. A company’s inability to sustain robust solvency portends the firm’s sick state that impairs its organic growth rate. Firms’ improper utilization of their unique characteristics as their corporate strategic drivers has given rise to illiquidity causing existential threat among listed firms in Nigeria. This study examines the effect of firms’ characteristics on solvency of selected listed companies in Nigeria. The study adopted ex-post facto research design. The population of the study was 161 listed companies in Nigeria as at 31st December 2020 with a chosen sample size of 111 purposively determined. Secondary data extracted from the published audited financial statements covering a 10-year period (2011–2020) were used for the study. Descriptive and inferential (multiple regression) statistics were employed to analyze the data. Findings revealed that corporate strategic drivers had joint significant effects on short-term solvency and long-term solvency. The study concludes that corporate strategic drivers exert significant influence on solvency of listed firms in Nigeria. The study recommends that firms should continue to utilize their corporate strategic characteristics to drive their short-term and long-term solvency statuses. Keywords: Corporate Strategic Drivers, Financial strategy, Firms’ Characteristics, Long-term solvency, Short-term solvency

Acetabular cup placement and offset control in robotic total hip arthroplasty performed through the modified anterolateral approach.

The modified anterolateral approach (Röttinger) for total hip arthroplasty (THA) offers great advantages over conventional approaches, especially concerning early postoperative symptoms, which are mild and well tolerated by patients. Robotic-assisted implantation might facilitate rapid adoption of the modified anterolateral approach without exposing surgeons to risks encountered during the learning curve. This study posits that the use of robotic assistance in conjunction with the modified anterolateral approach for total hip arthroplasty (THA) can provide a substantial enhancement in the accuracy of cup placement in comparison to manual surgery. Thirty-two robotic-assisted THAs met the inclusion criteria and were matched to 32 conventional cases. Acetabular cup inclination, anteversion, limb-length discrepancy, and acetabular offset were assessed using certified planning software by two independent observers using pre- and postoperative anterior-posterior radiographs. Data was analyzed for normal distribution. Chi2 test was used to determine whether implanted acetabular cups that were within Lewinnek's safe zones were influenced by type of implantation. Effect size estimates and statistical power analysis were also performed to appreciate the appropriateness of the chosen sample size. Robotic-assisted implantation was found to significantly improve acetabular cup placement in terms of inclination (p < 0.001) but not anteversion (p = 0.783). Although mean postoperative limb-length discrepancy and mean acetabular offset did not differ between groups, a significantly smaller variance was found in the robotic-assisted group (p < 0.001) and (p = 0.04), respectively. There were no significant differences between the two groups in terms of consistently implanting the acetabular cup within the Lewinnek safe zones p = 0.641 for anteversion and p = 0.230 for inclination, respectively. Our results show that although robotic-assisted acetabular cup implantation performed through the modified anterolateral approach did not significantly differ from conventional implantation, it did offer increased accuracy in cup positioning, acetabular bone preservation, and limb-length restoration.

AN EMPIRICAL STUDY OF CUSTOMER SATISFACTION TOWARDS E-BANKING SERVICES IN DELHI

Digital solutions are a must for Gen Next banking. There has been a surge in tech-enabled digital payments marking a shift in the operations of banks vis-a-vis technology and customer behavioural patterns. The last two years have witnessed a significant rise in digital transactions from 40 billion in 2020 to 87 billion in 2021 in India. Given the increasing preference for contactless banking, banks need to understand their customers better. The purpose of the study is to gauge customer perception towards e-banking services. The study uses the following variables, namely, user interface, content, communication, responsiveness, customer support services, data protection and recommendation of banks to others to find out the relationship with the age of the customers. The questionnaire method is used for conducting the study with a sample size of 200 customers. The cross-tabulation statistical test is applied using SPSS software for data analysis. The study covers the post-pandemic period and chalks out the strategies to increase digitalization in the banking industry which is required for the sector to flourish. Key findings indicate that the banking industry's current framework needs to find secure solutions to reduce online crimes and e-banking fraud. Based on the findings, better instruments and mechanisms for e-banking services must be put in place. It is recommended to develop a customized user interface for e-banking applications, enforce cyber laws and regulations to curb e-banking frauds and assist customers by setting up in-house cyber redressal cells. Based on time constraints, the study is limited only to 200 customers and the findings rest on the opinion and perception of our chosen sample size.

Practical approaches to Bayesian sample size determination in non-inferiority trials with binary outcomes.

Bayesian analysis of a non-inferiority trial is advantageous in allowing direct probability statements to be made about the relative treatment difference rather than relying on an arbitrary and often poorly justified non-inferiority margin. When the primary analysis will be Bayesian, a Bayesian approach to sample size determination will often be appropriate for consistency with the analysis. We demonstrate three Bayesian approaches to choosing sample size for non-inferiority trials with binary outcomes and review their advantages and disadvantages. First, we present a predictive power approach for determining sample size using the probability that the trial will produce a convincing result in the final analysis. Next, we determine sample size by considering the expected posterior probability of non-inferiority in the trial. Finally, we demonstrate a precision-based approach. We apply these methods to a non-inferiority trial in antiretroviral therapy for treatment of HIV-infected children. A predictive power approach would be most accessible in practical settings, because it is analogous to the standard frequentist approach. Sample sizes are larger than with frequentist calculations unless an informative analysis prior is specified, because appropriate allowance is made for uncertainty in the assumed design parameters, ignored in frequentist calculations. An expected posterior probability approach will lead to a smaller sample size and is appropriate when the focus is on estimating posterior probability rather than on testing. A precision-based approach would be useful when sample size is restricted by limits on recruitment or costs, but it would be difficult to decide on sample size using this approach alone.

Estimating the Shape Parameter of the Exponential-Weibull Distribution using Bayesian Technique

The Exponenial-Weibull Distribution (EWD) has been found to be useful in modeling and prediction of real life events. Its three parameter property makes it more flexible in modeling/accommodating dataset of different characteristics. However, Bayesian technique which is more robust and efficient in most cases, has not been used to estimate the shape parameter of this very important distribution. In view of this, Bayesian technique has been employed to estimate the shape parameter of the distribution. The performance of the technique is assessed and compared with that of maximum likelihood using Monte-carlo simulation. One informative and two non-informative priors as well as three loss functions were used for the study. The results showed that; Bayesian technique produced estimators with lower MSEs regardless of the chosen sample size and parameter value.

Impact of Tax Reforms on Economic Growth of Nigeria (2000-2021)

Abstract: Purpose: The objective of this study was to investigate the impact of tax reforms on economic growth of Nigeria. Methodology: This study adopted time series strategy basically concerned with how to perform impact analysis on already existing data. Secondary data were used in this study. However, relevant data for the study were obtained from Central Bank of Nigeria (CBN) Statistical Bulletins, Federal Inland Revenue Services Bulletins, and the World Bank, using judgmental sampling technique, a sample of 21 years’ period from 2000 to 2021. Regression analysis technique was used to measure the effects of the predictor variables on the criterion variables. This study used estimated technique of both descriptive statistics and Ordinary least square (OLS) regression analysis method with the help of Statistical Package for Social Sciences (SPSS 25). Results: The researcher revealed that there is a positive significant impact of VAT, CIT, &amp; PPT on RGDP in Nigeria among other things. Therefore, the researcher established that there is a significant positive impact of tax reforms on Nigeria’s economic growth. Contribution: The study's researcher suggested that policymakers should focus on boosting the productive capacity of the economy by reforming the tax code to prioritize economic growth and opportunity, government should expand the tax yield through improved tax administration system. This is because of the danger of over-reliance on crude oil export receipts to drive the economy among other things. Limitations: One of the limitations encountered in this study is that the chosen sample size was limited to one economy in Africa which is Nigeria. Keywords: 1. Tax Reforms 2. Economic Growth 3. Value Added Tax 4. Real Gross Domestic Product

To collapse or not to collapse blastocysts before vitrification? A matched case-control study on single vitrified-warmed blastocyst transfers

Research questionDoes laser-induced artificial blastocoel collapse result in better blastocyst cryopreservation survival and a higher live birth rate (LBR) in comparison with intact counterparts? DesignHalf of the supernumerary blastocysts from IVF cycles were randomly selected before vitrification for laser-induced artificial collapsing or vitrification in intact form. A matched case-control study of first transfers of single blastocysts artificially collapsed (case) or intact (control) before vitrification was conducted. Controls were matched to cases on a 1:1 ratio by female age, parity, fresh and vitrified cycle protocol, blastocyst age and quality, resulting in 309 case-control pairs. ResultsThe two groups were comparable in terms of their characteristics. Survival rates in the case and control groups (97.8% and 95.7%; P = 0.133) were comparable, but the optimal survival rate was higher in the case group (78.2% and 69.3%; P = 0.03). Clinical pregnancy rates (38.2% and 35.3%; P = 0.518), miscarriage rates (15.2% and 22%; P = 0.190), LBR per transfer (32.4% and 27.5%; P = 0.221) and LBR per warmed blastocyst (31.6% and 26.3%; P = 0.137) were not statistically different between the case and control groups. No significant difference in preterm births (11.1% versus 15.7%), birthweights (3333 ± 723 g versus 3304 ± 609 g) or sex ratio (49.3% versus 50.7% boys) was observed between the two groups. No major malformations were detected in the study population. ConclusionsCompared with vitrification of intact blastocysts, collapsed blastocysts resulted in a significantly higher optimal survival rate, and although they resulted in a 5% higher LBR, this was not significant for the chosen sample size. Neonatal outcomes were comparable in the two groups.

Impact of Management Control Systems on Sustainability of Agricultural Small and Medium Firms: Mediating Role of Corporate Social Responsibility (CSR) Practices

Purpose: The purpose of this paper is to determine the impact of management control systems such as self-control and organization’s norms on the sustainability of an organization with mediating role of corporate social responsibility (CSR) practices. The study focused on small and medium enterprises in the agricultural sector and how they can be sustainable by using these factors.&#x0D; Design/Methodology/Approach: This is a primary study based on quantitative data. The non-probability, convenience sampling is used. The research design includes hypotheses testing whether they are accepted or rejected. Data collection was done through closed-ended questionnaires with a Likert scale. The chosen sample size was 200 however, 184 questionnaires were received back after filling. Smart PLS was used for data analysis.&#x0D; Findings: Based on the analysis, all the hypotheses were accepted which show that there is indeed an impact of management control systems and organizations norms on an organization’s sustainability and CSR practices play the role of mediator.&#x0D; Implications/Originality/Value: Originality this study is testing the mediating effect of CSR practices on control systems, organizations norms and sustainability of the firm in the agricultural sector of Pakistan where small and medium enterprises related to the agricultural sector are targeted. There are very few researches that focused on SME’S in the agricultural sector of Pakistan, this study provided a detailed insight into this sector. The study will be of great value to agricultural and SME’s owners on how they can create sustainability in their firm.

Weather Variability Induced Uncertainty of Contrail Radiative Forcing

Persistent contrails and contrail cirrus are estimated to have a larger impact on climate than all CO2 emissions from global aviation since the introduction of jet engines. However, the measure for this impact, the effective radiative forcing (ERF) or radiative forcing (RF), suffers from uncertainties that are much larger than those for CO2. Despite ongoing research, the so called level of scientific understanding has not improved since the 1999 IPCC Special Report on Aviation and the Global Atmosphere. In this paper, the role of weather variability as a major component of the uncertainty range of contrail cirrus RF is examined. Using 10 years of MOZAIC flights and ERA-5 reanalysis data, we show that natural weather variability causes large variations in the instantaneous radiative forcing (iRF) of persistent contrails, which is a major source for uncertainty. Most contrails (about 80%) have a small positive iRF of up to 20 W m−2. IRF exceeds 20 W m−2 in about 10% of all cases but these have a disproportionally large climate impact, the remaining 10% have a negative iRF. The distribution of iRF values is heavily skewed towards large positive values that show an exponential decay. Monte Carlo experiments reveal the difficulty of determining a precise long-term mean from measurement or campaign data alone. Depending on the chosen sample size, calculated means scatter considerably, which is caused exclusively by weather variability. Considering that many additional natural sources of variation have been deliberately neglected in the present examination, the results suggest that there is a fundamental limit to the precision with which the RF and ERF of contrail cirrus can be determined. In our opinion, this does not imply a low level of scientific understanding; rather the scientific understanding of contrails and contrail cirrus has grown considerably over recent decades. Only the determination of global and annual mean RF and ERF values is still difficult and will probably be so for the coming decades, if not forever. The little precise knowledge of the RF and ERF values is, therefore, no argument to postpone actions to mitigate contrail’s warming impact.

Appropriate sampling strategies to estimate sea lice prevalence on salmon farms with low infestation levels

Effective sampling is essential to monitoring and controlling sea lice infestations on salmon farms. However, official sampling regimes are often inadequate, typically adopting a one-size-fits-all approach. Over the past decade, the thresholds at which mandatory treatment is required has also been reduced in many regions and, as such, the total infestation loads reported from salmon farms tend to be lower. Therefore, the use of prevalence, as opposed to the more conventionally used abundance, becomes a metric of interest and, from an analytical perspective, offers some beneficial characteristics. This paper explores a range of sampling scenarios and their impacts on the accuracy of sea lice estimation, particularly when prevalence is the adopted metric.Empirical sea lice count data demonstrated a good fit to the negative binomial distribution and provided a probable range of values that could be used to describe typical levels of over-dispersion. It was demonstrated that, when prevalence is low, it can be reliably used to predict abundance. Monte Carlo simulations of a hypothetical salmon farm were then used to test results for a variety of sample sizes and sea lice infestation scenarios. Different sea lice infestation levels between pens in a farm (i.e. a spatial clustering effect) and aggregations of sea lice on their hosts (i.e. the effect of over-dispersion) were simulated to explore a variety of conditions. The extent to which higher levels of clustering and/or over-dispersion necessitate the need for larger sample sizes to achieve similar levels of accuracy was explored. The level of accuracy that can be achieved in practice depends on many factors and what is considered to be an acceptable level of accuracy will, by definition, be subjective and vary according to the purpose for which the estimation is being carried out. This study includes a variety of possible situations to guide farm operators in choosing sample sizes according to their particular requirements. Furthermore, appropriate sample size determination can be expected to reduce overall sampling effort, achieve better overall control, help avoid unnecessary treatments, and reduce both associated costs and fish welfare impacts.

Effect of Secondary School Categorization on Examination Failure Rates Among Public Secondary Schools Students in Kenya

Secondary schools in Kenya are categorized as national, extra-county, county, sub-county and private secondary schools. Students who excelled in K.C.S.E examination with a minimum grade of C+ are allowed to pursue different courses in public and private universities. Others who scored C and C- grade joined diploma colleges. The paper sought to find out the effect of secondary school categorization on examination failure rates among public secondary schools students in Kenya. The scope of the study was limited to all the students from public secondary schools in the four counties of Kakamega, Bungoma, Busia, and Vihiga in Kenya. It was limited to randomly chosen sample size of 464 students, 58 principals, and 58 directors of studies from the 58 sampled out public secondary schools. Wellberg’s (1981) theory of educational productivity was employed. The paper employed mixed methods and survey research design. Data collection instruments included questionnaires, interview schedules, focused group discussions and analysis of secondary data. Content validity was determined through subject matter expert review while reliability was determined through test-retest measures for consistency. Descriptive and inferential statistics were used to analyze data. Inferential one was the Kruskal Wallis test. The paper concluded that secondary school categorization led to failure of students in public secondary schools at KCSE examinations in Kenya due to academic inadequacies experienced in sub-county and some county public secondary schools. It was therefore recommended that the classification of students into the four distinct groups of national, Extra County, county and sub county students be abolished. Keywords: academic achievement, Analysis, categorization, effect, Public s econdary school DOI : 10.7176/JEP/10-33-03 Publication date: November 30 th 2019

Effect of Secondary School Categorization on Value Addition in Public Secondary Schools Students in Kenya

Secondary schools in Kenya are categorized as national, extra-county, county, sub-county and private secondary schools. Students who excelled in K.C.S.E examination with a minimum grade of C+ are allowed to pursue different courses in public and private universities. Others who scored C and C- grade joined diploma colleges. The paper sought to establish the effect of secondary school categorization on academic value addition in public secondary schools students at fourth form in Kenya. The scope of the study was limited to all the students from public secondary schools in the four counties of Kakamega, Bungoma, Busia, and Vihiga in Kenya. It was limited to randomly chosen sample size of 464 students, 58 principals, and 58 directors of studies from the 58 sampled out public secondary schools. Wellberg’s (1981) theory of educational productivity was employed. The paper employed mixed methods and survey research design. Data collection instruments included questionnaires, interview schedules, focused group discussions and analysis of secondary data. Content validity was determined through subject matter expert review while reliability was determined through test-retest measures for consistency. Descriptive and inferential statistics were used to analyze data. Inferential one was the Kruskal Wallis test. The paper findings showed that value addition in public secondary schools in Kenya was not based on secondary school characteristics. The study concluded that irrespective of the score at KCPE and the category of public secondary school a student is admitted after KCPE, a student can add academic value. It was therefore recommended public secondary school characteristics which allowed student improvement at national and extra county school levels more than at sub-county and county secondary schools levels should be duplicated at county and sub county school levels. Keywords: academic value addition, categorization, effect, Public s econdary school, students DOI : 10.7176/JEP/10-33-12 Publication date: November 30 th 2019

Economic Analysis of Optimal Sample Size in Legal Proceedings

In many legal settings, a statistical sample can be an effective surrogate for a larger population when adjudicating questions of causation, liability, or damages. The current paper works through salient aspects of statistical sampling and sample size determination in legal proceedings. An economic model is developed to provide insight into the behavioral decision-making about sample size choice by a party that intends to offer statistical evidence to the court. The optimal sample size is defined to be the sample size that maximizes the expected payoff of the legal case to the party conducting the analysis. Assuming a probability model that describes a hypothetical court&amp;rsquo;s likelihood of accepting statistical evidence based on the sample size, the optimal sample size is reached at a point where the increase in the probability of the court accepting the sample from a unit increase in the chosen sample size, multiplied by the payoff from winning the case, is equal to the marginal cost of increasing the sample size.

Choosing sample sizes for various blood parameters of broiler chickens with normal and non-normal observations.

Experimental power is a measure of the ability of an experiment to detect differences between treatment means. Researchers design experiments and then calculate the probability that differences are simply due to chance, the null hypothesis. The objective of the analyses reported here was to determine the appropriate number of samples to demonstrate significant differences of various magnitudes from broiler chicken blood constituents. Over 800 samples were taken for a study of the effects of sample storage time, serum vs. plasma, light intensity, and fed vs. fasted birds on blood cholesterol, triglycerides, uric acid, glucose, total protein (TP), albumin, globulin, alanine aminotransferase (ALT), aspartate aminotransferase, gammaGT, creatinine, alkaline phosphatase, Ca and P. Various transformations increased the QQ plot R2 values from 0.000 to 0.149 or 0.00 to 17.62%. Most of the QQ plot R2 values were at or above 0.90. The 1/x2 transformation of blood P data showed the biggest increase in QQ plot R2 (0.846 to 0.995). The different standard deviations and coefficients of variation (CVs) found for each variable resulted in widely different numbers of replicates needed to detect differences in 2 treatment means. The extremes were glucose with a CV of 6.9% and ALT with a CV of 39.7%. For glucose, 15 replicates are needed to find a 10% difference in 97% of experiments; for ALT, 15 replicates would detect a 50% difference 91% of the time. The use of parameters such as cholesterol, glucose, TP, albumin, and globulin showed low CVs, indicating they may be considered as stable parameters. The lower CVs make it possible to find differences with a smaller number of replicates used in studies. As reported, the phosphorus values did not have a normal distribution of the data, so a transformation of these data could be an alternative to better discuss the results found.

Current practice in methodology and reporting of the sample size calculation in randomised trials of hip and knee osteoarthritis: a protocol for a systematic review

BackgroundA key aspect of the design of randomised controlled trials (RCTs) is determining the sample size. It is important that the trial sample size is appropriately calculated. The required sample size will differ by clinical area, for instance, due to the prevalence of the condition and the choice of primary outcome. Additionally, it will depend upon the choice of target difference assumed in the calculation. Focussing upon the hip and knee osteoarthritis population, this study aims to systematically review how the trial size was determined for trials of osteoarthritis, on what basis, and how well these aspects are reported.MethodsSeveral electronic databases (Medline, Cochrane library, CINAHL, EMBASE, PsycINFO, PEDro and AMED) will be searched to identify articles on RCTs of hip and knee osteoarthritis published in 2016. Articles will be screened for eligibility and data extracted independently by two reviewers. Data will be extracted on study characteristics (design, population, intervention and control treatments), primary outcome, chosen sample size and justification, parameters used to calculate the sample size (including treatment effect in control arm, level of variability in primary outcome, loss to follow-up rates). Data will be summarised across the studies using appropriate summary statistics (e.g. n and %, median and interquartile range). The proportion of studies which report each key component of the sample size calculation will be presented. The reproducibility of the sample size calculation will be tested.DiscussionThe findings of this systematic review will summarise the current practice for sample size calculation in trials of hip and knee osteoarthritis. It will also provide evidence on the completeness of the reporting of the sample size calculation, reproducibility of the chosen sample size and the basis for the values used in the calculation.Trial registrationAs this review was not eligible to be registered on PROSPERO, the summary information was uploaded to Figshare to make it publicly accessible in order to avoid unnecessary duplication amongst other benefits (https://doi.org/10.6084/m9.figshare.5009027.v1); Registered January 17, 2017.