Assessment of therapeutic equivalence or non-inferiority between two medical diagnostic procedures often involves comparisons of the response rates between paired binary endpoints. The commonly used and accepted approach to assessing equivalence is by comparing the asymptotic confidence interval on the difference of two response rates with some clinical meaningful equivalence limits. This paper investigates two asymptotic test statistics, a Wald-type (sample-based) test statistic and a restricted maximum likelihood estimation (RMLE-based) test statistic, to assess equivalence or non-inferiority based on paired binary endpoints. The sample size and power functions of the two tests are derived. The actual type I error and power of the two tests are computed by enumerating the exact probabilities in the rejection region. The results show that the RMLE-based test controls type I error better than the sample-based test. To establish an equivalence between two treatments with a symmetric equivalence limit of 0.15, a minimal sample size of 120 is needed. The RMLE-based test without the continuity correction performs well at the boundary point 0. A numerical example illustrates the proposed procedures.

Linearity is one of the most important characteristics for evaluation of the accuracy in assay validation. The current statistical method for evaluation of the linearity recommended by the Clinical Laboratory Standard Institute (CLSI) guideline EP6-A is reviewed. The method directly compares the point estimates with the pre-specified allowable limit and completely ignores the sampling error of the point estimates. An alternative method for evaluation of linearity, proposed by Kroll et al. (2000), considers the statistical test procedure based on the average deviation from linearity (ADL). However this procedure is based on an inappropriate formulation of hypotheses for the evaluation of linearity. Consequently, the type I error rates of both current methods may be inflated for inference of linearity. To claim the linearity of analytical methods, we propose that the hypothesis of proving the linearity should be formulated as the alternative hypothesis. Furthermore, any procedures for assessment of linearity should be based on the sampling distributions of the proposed test statistics. Therefore, we propose a two one-sided test (TOST) procedure and a corrected Kroll's procedure. The simulation studies were conducted to empirically compare the size and power between current and proposed methods. The simulation results show that the proposed methods not only adequately control size but also provide sufficient power. A numeric example illustrates the proposed methods.

One of the most important characteristics for evaluation of the accuracy in assay validation is the linearity. Kroll, et al.[1] proposed a method based on the average deviation from linearity (ADL) to evaluate the linearity. Hsieh and Liu [2] suggested that hypothesis for proving the linearity be formulated as the alternative hypothesis and proposed the corrected Kroll's method. However, the issue concerning the variability in estimation of the non-centrality parameter is still unresolved. Consequently, the type I error rates may still be inflated for the corrected Kroll's method. To overcome this issue, we propose the sum of squares of deviations from linearity (SSDL) as an alternative metric for evaluation of linearity. Based on SSDL, we applied the method of generalized pivotal quantities (GPQ) for the inference of evaluation of linearity. The simulation studies were conducted to empirically investigate the size and power between current and proposed methods. The simulation results show that the proposed GPQ method not only adequately control size but also provide sufficient power than other methods. A numeric example illustrates the proposed methods.

In general, the poor thermal insulation of building materials usually causes elevated room temperature, which not only reduces the comfort of the environment but also adds extra loading to the air conditioner. The objective of this study is to investigate the heat insulation efficiencies of building outer skins used for green building. A total of 25 types of multi-layer cladding materials and 9 types of single-layer skin materials made in Taiwan along with 4 types of overseas multi-layer skin materials were tested using the hot box method (HBM). The above data were then adopted to calculate the heat-insulation ability, vapor transmission volume and heat gain cooling load. Besides, the costs of the above materials were also collected to provide useful information for green building industry to select the most proper skin materials in considering both the material performance and costs. The analysis results suggest that the ‘k’ group (paint-baked metal plate + 2” 100 k rock wool + paint-baked metal plate) exhibits the best heat-insulating capacity, which is 67.0%. However, Item 15 (colour corrugated steel plate + conventional steel bearing plate + calcium silicate board) presents the smallest moisture-permeable amount at 0.001 g/h. Besides, Item ‘13’ exhibits the smallest cooling load, which is 1.8 W. From the above, it is shown that superior heat-insulating performance does not necessarily mean better moisture permeability resistance. The skin material which presents superior moisture permeability resistance does not always present a higher cooling load. For this reason, the appropriate skin materials should be selected by matching with the climatic environment where the building is located. Moreover, the decrement of CO2 emissions caused by transportation is also another key point which the green building industry should consider. Practical application: The objectives of this research are to investigate the heat insulation efficiencies of building outer skins used in the green buildings. The heat capacity, moisture-permeable resistance, solar heat gain cooling load and costs of the building outer skins frequently used in Taiwan have been calculated and collected in this study. Therefore, the engineers and building industry can choose the most suitable materials with the help of the above information.

Similarity of the treatment effects of a drug product among different intrinsic and extrinsic ethnic, geographic, or demographic factors is important not only to regulatory agencies in the approval of the drug but also to the public health. Examples include bridging studies in different regions, the extrapolation from the adult population to the pediatric subpopulation, or comparisons between different geographic regions within a global trial. It is an issue of evaluation of the treatment-by-factor interaction. Howevq assessment of similarity Global Trialsis not to detect the existence of treatment-byfactor interaction but rather to evaluate whether the magnitude of treatment-by-factor interaction is within a clinically allowable margin. As a result, we propose two testing procedures for the noninfen'ority hypothesis of the treatment-by-factor interaction to assess the similarity of the treatment effects among ethnical or demographic factors. Two numeric data sets illustrate applications of the proposed methods to different scenarios under diffment circumstances.