Trends in private and public investments in agricultural marketing infrastructure in India

The study has estimated the extent of investment made in promotion of marketing infrastructure in the country and growth in public and private investments. It has also examined state-wise spread of private and public investments in agricultural marketing infrastructure, its composition and share and has investigated whether private investment induces pubic investment or vice versa. Of the total investment of Rs 157652.30 lakh made for the development of agricultural marketing infrastructure, Madhya Pradesh has accounted for the maximum (36%) share, followed by Tamil Nadu (18%) and Andhra Pradesh (13.5%). West Bengal has accounted for the lowest share. The analysis has indicated that there is a strong complementarity between private and public investments and as soon as private investment comes, public investment also starts pouring in. On investigating whether public investment is dependent on private investment or vice versa, the study has revealed that private investment induces public investment. The study has further indicated that in agricultural marketing infrastructure, private investment has taken a lead, which is a welcome change because private investment is more efficiently used as compared to public investment. To give further fillip to private investment in agricultural marketing infrastructure, the study has provided certain suggestions.Marketing,

Update on the transfusion in gastrointestinal bleeding (TRIGGER) trial: statistical analysis plan for a cluster-randomised feasibility trial

BACKGROUND: Previous research has suggested an association between more liberal red blood cell (RBC) transfusion and greater risk of further bleeding and mortality following acute upper gastrointestinal bleeding (AUGIB). METHODS AND DESIGN: The Transfusion in Gastrointestinal Bleeding (TRIGGER) trial is a pragmatic cluster-randomised feasibility trial which aims to evaluate the feasibility of implementing a restrictive vs. liberal RBC transfusion policy for adult patients admitted to hospital with AUGIB in the UK. This trial will help to inform the design and methodology of a phase III trial. The protocol for TRIGGER has been published in Transfusion Medicine Reviews. Recruitment began in September 2012 and was completed in March 2013. This update presents the statistical analysis plan, detailing how analysis of the TRIGGER trial will be performed. It is hoped that prospective publication of the full statistical analysis plan will increase transparency and give readers a clear overview of how TRIGGER will be analysed. TRIAL REGISTRATION: ISRCTN85757829

Evolution of treatment targets in Crohn’s disease

Crohn’s disease is a chronic relapsing and remitting inflammatory disorder of the gastrointestinal tract, associated with significantly morbidity due to both symptoms and complications that have a considerable detrimental impact on a patient’s quality of life. An early treat to target approach with disease modifying agents has been shown to significantly improve long term outcomes, demonstrated by a number of therapeutic targets in a number of modalities. This review will outline the current treatment targets and measures of disease burden in Crohn’s disease

Pre-specification of statistical analysis approaches in published clinical trial protocols was inadequate

OBJECTIVES: Results from randomized trials can depend on the statistical analysis approach used. It is important to prespecify the analysis approach in the trial protocol to avoid selective reporting of analyses based on those which provide the most favourable results. We undertook a review of published trial protocols to assess how often the statistical analysis of the primary outcome was adequately prespecified. METHODS: We searched protocols of randomized trials indexed in PubMed in November 2016. We identified whether the following aspects of the statistical analysis approach for the primary outcome were adequately prespecified: (1) analysis population; (2) analysis model; (3) use of covariates; and (4) method of handling missing data. RESULTS: e identified 99 eligible protocols. Very few protocols adequately prespecified the analysis population (8/99, 8%), analysis model (27/99, 27%), covariates (40/99, 40%), or approach to handling missing data (10/99, 10%). Most protocols did not adequately predefine any of these four aspects of their statistical analysis approach (39%) or predefined only one aspect (36%). No protocols adequately predefined all four aspects of the analysis. CONCLUSION: The statistical analysis approach is rarely prespecified in published trial protocols. This may allow selective reporting of results based on different analyses

Barriers to Information and Digital Technologies Adoption in Humanitarian Supply Chain Management : A Fuzzy AHP Approach

Peer reviewedPostprin

Is Market Really Efficient?

Abstract Market efficiency is the degree to which stock prices reflect all available and relevant information. The th eory of market efficiency says that the stock market reacts very quickly to the new information and represents the sum of the information available and choi ces made by traders and investors. There is a well known an well accepted phenomena, Efficient Market Hypothesis, which states that market prices incorporate all information rationally and instantly but is this really so? Do markets really behave rationally or are driven by fear and greed? The present paper is an attempt to reconcile market efficiency with actual behaviour of investors by taking recent research in the cognitive neuroscience that has been transforming and revitalizing the interaction of psychology and economies, as the base. The present paper is a theoretical work based on the literature reviewed on the efficient market hypothesis. There are some other more promising alternatives to Efficient Market Hypothesis like Behavioral Psychology Approaches to stock market trading. The present paper would try to highlight some of these alternatives and justify whether the Efficient Market Hypothesis hold really true and whether the market is really efficient

Access to unpublished protocols and statistical analysis plans of randomised trials

Background: Access to protocols and statistical analysis plans (SAPs) increases the transparency of randomised trial by allowing readers to identify and interpret unplanned changes to study methods, however they are often not made publicly available. We sought to determine how often study investigators would share unavailable documents upon request. Methods: We used trials from two previously identified cohorts (cohort 1: 101 trials published in high impact factor journals between January and April of 2018; cohort 2: 100 trials published in June 2018 in journals indexed in PubMed) to determine whether study investigators would share unavailable protocols/SAPs upon request. We emailed corresponding authors of trials with no publicly available protocol or SAP up to four times. Results: Overall, 96 of 201 trials (48%) across the two cohorts had no publicly available protocol or SAP (11/101 high-impact cohort, 85/100 PubMed cohort). In total, 8/96 authors (8%) shared some trial documentation (protocol only [n = 5]; protocol and SAP [n = 1]; excerpt from protocol [n = 1]; research ethics application form [n = 1]). We received protocols for 6/96 trials (6%), and a SAP for 1/96 trial (1%). Seventy-three authors (76%) did not respond, 7 authors responded (7%) but declined to share a protocol or SAP, and eight email addresses were invalid (8%). A total of 329 emails were sent (an average of 41 emails for every trial which sent documentation). After emailing authors, the total number of trials with an available protocol increased by only 3%, from 52% in to 55%. Conclusions: Most study investigators did not share their unpublished protocols or SAPs upon direct request. Alternative strategies are needed to increase transparency of randomised trials and ensure access to protocols and SAPs

Lactobacillus fermentum (PCC®) supplementation and gastrointestinal and respiratory-tract illness symptoms: a randomised control trial in athletes

BACKGROUND Probiotics purportedly reduce symptoms of gastrointestinal and upper respiratory-tract illness by modulating commensal microflora. Preventing and reducing symptoms of respiratory and gastrointestinal illness are the primary reason that dietary supplementation with probiotics are becoming increasingly popular with healthy active individuals. There is a paucity of data regarding the effectiveness of probiotics in this cohort. The aim of this study was to evaluate the effectiveness of a probiotic on faecal microbiology, self-reported illness symptoms and immunity in healthy well trained individuals. METHODS Competitive cyclists (64 males and 35 females; age 35 ± 9 and 36 ± 9 y, VO2max 56 ± 6 and 52 ± 6 ml.kg-1.min-1, mean ± SD) were randomised to either probiotic (minimum 1 × 109 Lactobacillus fermentum (PCC®) per day) or placebo treatment for 11 weeks in a double-blind, randomised, controlled trial. The outcome measures were faecal L. fermentum counts, self-reported symptoms of illness and serum cytokines. RESULTS Lactobacillus numbers increased 7.7-fold (90% confidence limits 2.1- to 28-fold) more in males on the probiotic, while there was an unclear 2.2-fold (0.2- to 18-fold) increase in females taking the probiotic. The number and duration of mild gastrointestinal symptoms were ~2-fold greater in the probiotic group. However, there was a substantial 0.7 (0.2 to 1.2) of a scale step reduction in the severity of gastrointestinal illness at the mean training load in males, which became more pronounced as training load increased. The load (duration×severity) of lower respiratory illness symptoms was less by a factor of 0.31 (99%CI; 0.07 to 0.96) in males taking the probiotic compared with placebo but increased by a factor of 2.2 (0.41 to 27) in females. Differences in use of cold and flu medication mirrored these symptoms. The observed effects on URTI had too much uncertainty for a decisive outcome. There were clear reductions in the magnitude of acute exercise-induced changes in some cytokines. CONCLUSION L. fermentum may be a useful nutritional adjunct for healthy exercising males. However, uncertainty in the effects of supplementation on URTI and on symptoms in females needs to be resolved. TRIAL REGISTRATION The trial was registered in the Australia and New Zealand Clinical Trials Registry (ACTRN12611000006943).The study was funded by Christian Hansen A/S, Probiomics and the Australian Institute of Sport

FACTORS AFFECTING THE INDIAN GARMENT EXPORTERS IN LUDHIANA TO HEDGE THEIR FOREIGN EXCHANGE RISK

In todays world of Globalization where large number of firms is entering the international markets, they are being continuously facing risk due to foreign exchange rate volatility. Consequently, they are start using hedging tools for managing foreign exchange risk. But there are still lot of firms who are not using hedging tools for some unknown reasons. This study aimed at analyzing the factors that are affecting the decision of Indian garments exporters in Ludhiana to hedge their foreign exchange risk exposure. Information has been obtained by conducting primary research on garment exporters in Ludhiana, to determine the reasons why they are using hedging tools for foreign exchange risk management. As the currency derivatives market is still at an emerging stage in India, the use of hedging instruments is a new concept for the firms, which is gaining popularity day by day. The findings show that there are lot of factors like infrastructure which are acting as an obstacle in their decision to hedge. The study also given the reasons behind each factor and how these garment exporters are reacting to it. Eventually, the paper provides a significant way for future study, which requires a quantitative analysis to be carried out on the fully disclosed data, in order to identify their outlook behind hedging activities

Adjusting for multiple prognostic factors in the analysis of randomised trials

Background: When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method. Methods: We used simulation to (1) determine if a stratified analysis is necessary after stratified randomisation, and (2) to compare different methods of adjustment in terms of power and type I error rate. We considered the following methods of analysis: adjusting for covariates in a regression model, adjusting for each stratum using either fixed or random effects, and Mantel-Haenszel or a stratified Cox model depending on outcome. Results: Stratified analysis is required after stratified randomisation to maintain correct type I error rates when (a) there are strong interactions between prognostic factors, and (b) there are approximately equal number of patients in each stratum. However, simulations based on real trial data found that type I error rates were unaffected by the method of analysis (stratified vs unstratified), indicating these conditions were not met in real datasets. Comparison of different analysis methods found that with small sample sizes and a binary or time-to-event outcome, most analysis methods lead to either inflated type I error rates or a reduction in power; the lone exception was a stratified analysis using random effects for strata, which gave nominal type I error rates and adequate power. Conclusions: It is unlikely that a stratified analysis is necessary after stratified randomisation except in extreme scenarios. Therefore, the method of analysis (accounting for the strata, or adjusting only for the covariates) will not generally need to depend on the method of randomisation used. Most methods of analysis work well with large sample sizes, however treating strata as random effects should be the analysis method of choice with binary or time-to-event outcomes and a small sample size