The primary aim of clinical trials is to investigate whether a treatment is effective for a particular disease or condition. Randomized controlled clinical trials are considered to be the gold standard for evaluating ...The primary aim of clinical trials is to investigate whether a treatment is effective for a particular disease or condition. Randomized controlled clinical trials are considered to be the gold standard for evaluating the effect of a certain intervention. However, in clinical trials, even after randomization, there are situations where the patients differ substantially with respect to the baseline value of the outcome variable. Many a times the response to interventions depends on the baseline values of the outcome variable. When there are baseline-dependent treatment effects, differences among treatments vary as a function of baseline level. Although variation in outcome associated with baseline value is accounted for in ANCOVA, analysis of individual differences in treatment effect is precluded by the homogeneity of regression assumption. This assumption requires that expected differences in outcome among treatments be constant across all baseline levels. To overcome this difficulty, Weigel and Narvaez [7] proposed a regression model for two treatment groups to analyze individual response to treatments in randomized controlled clinical trials. The authors reviewed the model suggested by Weigel and Narvaez and extended further for three or more treatment groups. The utility of the model was demonstrated with real life data from a randomized controlled clinical trial of bronchial asthma.展开更多
Often many variables have to be analyzed for their importance in terms of significant contribution and predictability in medical research. One of the possible analytical tools may be the Multiple Linear Regression Ana...Often many variables have to be analyzed for their importance in terms of significant contribution and predictability in medical research. One of the possible analytical tools may be the Multiple Linear Regression Analysis. However, research papers usually report both univariate and multivariate regression analyses of the data. The biostatistician sometimes faces practical difficulties while selecting the independent variables for logical inclusion in the multivariate analysis. The selection criteria for inclusion of a variable in the multivariate regression is that the variable at the univariate level should have a regression coefficient with p 〈 0.20. However, there is a chance that an independent variable with p 〉 0.20 at univariate regression may become significant in the multivariate regression analysis and vice versa, provided the above criteria is not strictly adhered to. We undertook both univariate and multivariate linear regression analyses on data from two multi-centric clinical trials. We recommend that there is no need to restrict the p value of 〈= 0.20. Because of high speed computer and availability of statistical software, the desired results could be achieved by considering all relevant independent variables in multivariate regression analysis.展开更多
Geopolymers are inorganic adhesive synthesized from industrial waste such as fly ash thus the development of wood geopolymer composite would be a low carbon footprint material.Geopolymers,being a non-formaldehyde adhe...Geopolymers are inorganic adhesive synthesized from industrial waste such as fly ash thus the development of wood geopolymer composite would be a low carbon footprint material.Geopolymers,being a non-formaldehyde adhesive can be used as an alternative binder for wood based composites where environmentally friendly and sustainability of product is important.In this study flyash as precursor is been used in the development of wood geopolymer composite product.Flyash is activated with a combination of sodium hydroxide and sodium silicate solutions at a weight ratio of 1:2.5 for geopolymer formation.The study investigated the properties of wood geopolymer composite made with ratios of wood particle to flyash percentage(23/77),(37/62),(44/55),(50/50)and(57/43).Geopolymer formation was observed by X-ray Diffraction(XRD)and Fourier transform infrared spectroscopy(FTIR).Influence of wood particles in wood geopolymer composite were observed by Scanning electron microscope.The study shows that the water absorption and thickness selling properties of all the formulations of wood geopolymer composites are comparable with the medium density particle board and cement-bonded particleboard according to the IS:3087-2005 standard and IS:12406:respectively.Highest mechanical properties and good bond strength was obtained by the composite containing 23%wood particle ratio with 77%percent flyash.However,still improvement in mechanical properties is needed to achieve the mechanical properties comparable to cement bonded particle board.展开更多
文摘The primary aim of clinical trials is to investigate whether a treatment is effective for a particular disease or condition. Randomized controlled clinical trials are considered to be the gold standard for evaluating the effect of a certain intervention. However, in clinical trials, even after randomization, there are situations where the patients differ substantially with respect to the baseline value of the outcome variable. Many a times the response to interventions depends on the baseline values of the outcome variable. When there are baseline-dependent treatment effects, differences among treatments vary as a function of baseline level. Although variation in outcome associated with baseline value is accounted for in ANCOVA, analysis of individual differences in treatment effect is precluded by the homogeneity of regression assumption. This assumption requires that expected differences in outcome among treatments be constant across all baseline levels. To overcome this difficulty, Weigel and Narvaez [7] proposed a regression model for two treatment groups to analyze individual response to treatments in randomized controlled clinical trials. The authors reviewed the model suggested by Weigel and Narvaez and extended further for three or more treatment groups. The utility of the model was demonstrated with real life data from a randomized controlled clinical trial of bronchial asthma.
文摘Often many variables have to be analyzed for their importance in terms of significant contribution and predictability in medical research. One of the possible analytical tools may be the Multiple Linear Regression Analysis. However, research papers usually report both univariate and multivariate regression analyses of the data. The biostatistician sometimes faces practical difficulties while selecting the independent variables for logical inclusion in the multivariate analysis. The selection criteria for inclusion of a variable in the multivariate regression is that the variable at the univariate level should have a regression coefficient with p 〈 0.20. However, there is a chance that an independent variable with p 〉 0.20 at univariate regression may become significant in the multivariate regression analysis and vice versa, provided the above criteria is not strictly adhered to. We undertook both univariate and multivariate linear regression analyses on data from two multi-centric clinical trials. We recommend that there is no need to restrict the p value of 〈= 0.20. Because of high speed computer and availability of statistical software, the desired results could be achieved by considering all relevant independent variables in multivariate regression analysis.
基金We thank Indian plywood Industries research and training Institute,an autonomous body of Ministry of environment forest and climate change funded this research project.I thank my co-authors for helping me in the study,analysis,and interpretation of data and in writing the manuscript should be declared.
文摘Geopolymers are inorganic adhesive synthesized from industrial waste such as fly ash thus the development of wood geopolymer composite would be a low carbon footprint material.Geopolymers,being a non-formaldehyde adhesive can be used as an alternative binder for wood based composites where environmentally friendly and sustainability of product is important.In this study flyash as precursor is been used in the development of wood geopolymer composite product.Flyash is activated with a combination of sodium hydroxide and sodium silicate solutions at a weight ratio of 1:2.5 for geopolymer formation.The study investigated the properties of wood geopolymer composite made with ratios of wood particle to flyash percentage(23/77),(37/62),(44/55),(50/50)and(57/43).Geopolymer formation was observed by X-ray Diffraction(XRD)and Fourier transform infrared spectroscopy(FTIR).Influence of wood particles in wood geopolymer composite were observed by Scanning electron microscope.The study shows that the water absorption and thickness selling properties of all the formulations of wood geopolymer composites are comparable with the medium density particle board and cement-bonded particleboard according to the IS:3087-2005 standard and IS:12406:respectively.Highest mechanical properties and good bond strength was obtained by the composite containing 23%wood particle ratio with 77%percent flyash.However,still improvement in mechanical properties is needed to achieve the mechanical properties comparable to cement bonded particle board.
