Small Sample Properties of Rank Tests for Incomplete Unbalanced Designs

A rank test is presented for analysis of incomplete unbalanced designs, i.e. for designs that may have been originally planned to be either balanced or unbalanced and where some observations may be missing at random. This test is a modification of the procedure of Benard and van El-teren (1953) based on a generalization of block weights proposed by Prentice (1979). It is compared with the tests of Haux, Schumacher, and Weckesser (1984) and Rai (1987). For incomplete or unbalanced designs with more than two treatments the quadratic forms proposed by these authors are proven to be invalid for small sample sizes, except for special cases. A necessary condition is given for test statistics to be valid also for small samples.     

An Analysis of Variance of Nominal Data

This paper considers a common problem in analysis of variance where the responses to a set of treatments are nominal (i.e. are recorded in frequencies) with no underlying metric. Reasoning by analogy from standard analysis of variance of a two-way classification we develop chi-square tests for significance of treatments and interactions. Two tests are proposed for interaction and their asymptotic properties are studied.     

便携多路环境数据采集系统

便携多路环境数据采集系统姜仕仁，常杰，葛滢（杭州大学生物科学与技术系，３１００１２）ＡＰｏｒｔａｂｌｅＭｕｌｔｉ－ＰａｓｓａｇｅＥｎｖｉｒｏｎｍｅｎｔａｌＤａｔａＡｕｔｏ－ＳａｍｐｌｉｎｇＳｙｓｔｅｍ．￥ＪｉａｎｇＳｈｉｒｅｎ；ＣｈａｎｇＪｉｅ；Ｇｅ...     

Note on a method for analyzing stage-frequency data

A new method for analyzing stage-frequency data is proposed which is based on the estimation of rates of transition between one stage and the next highest stage in one unit of time, and a unit time survival rate that is assumed to be constant. Once these estimates are calculated it becomes possible to also estimate the mean durations of stages, stage-specific survival rates, and numbers entering stages. An advantage of the method is that it can be applied with any distribution of entry times to stage 1, and any distribution of numbers in stages when sampling begins. Use of the method is illustrated on data from a copepod population in a Canadian lake.     

Inclusion of phytosociological data in an index of vegetation fire danger: application and mapping on the Karst area around Trieste (Italy)

In this paper we propose a method to produce maps of fire danger index (FDI). The index includes in the formula a vegetation pyrogenic potential index (VPPI) based on floristic phytosociological data. The map of FDI is produced by integrating available phytosociological maps of vegetation, geomorphology and climate, using the Geographic Information System technology. The method is applied to an area of the coastal Classical Karst (NE-Italy). While fire risk maps based on the incidence of previous fires are useful for facilitating emergency operations, e.g. the allocation of fire fighting resources, we conclude that the proposed index offers an effective tool to plan actions for fire prevention.     

Initial Characterization of Micafungin Pulmonary Delivery via Two Different Nebulizers and Multivariate Data Analysis of Aerosol Mass Distribution Profiles

Pharmaceutical aerosols have been targeted to the lungs for the treatment of asthma and pulmonary infectious diseases successfully. Micafungin (Astellas Pharma US, Deerfield, IL, USA) has been shown to be an effective antifungal agent when administrated intravenously. Pulmonary delivery of micafungin has not previously been reported. In the present pilot study, we characterize the performance of two nebulizers and their potential for delivering micafungin to the lungs as well as the use of multivariate data analysis for mass distribution profile comparison. The concentration of micafungin sodium increased by 21% when delivered by the Acorn II nebulizer and by 20% when delivered by the LC Plus nebulizer, respectively, from the first to the second sampling period. The Acorn II nebulizer delivered a fine particle fraction FPF_5.8 (%<5.8 μm) of 92.5 ± 0.8 and FPF_3.3 (%<3.3 μm) of 82.3 ± 2.1 during the first sampling period. For the LC Plus nebulizer, FPF_5.8 was 92.3 ± 0.1 and FPF_3.3 was 67.0 ± 0.7 during the first sampling period. The mass median aerodynamic diameter (MMAD) increased from 1.67 ± 0.05 to 1.77 ± 0.04 μm (Acorn II nebulizer) and from 2.09 ± 0.01 to 2.20 ± 0.01 μm (Pari LC Plus nebulizer) from the first to the second sampling periods. These changes in MMAD were statistically significant by paired t test. Multivariate data analysis showed that this could be explained systematically by greater drug deposition on stages with larger cutoff sizes and reduced drug deposition on stages with smaller cutoff sizes rather than multimodal deposition or other anomalies in size distribution.     

Performance of the marginal structural models under various scenarios of incomplete marker's values: A simulation study

Marginal structural models (MSMs) have been proposed for estimating a treatment's effect, in the presence of time‐dependent confounding. We aimed to evaluate the performance of the Cox MSM in the presence of missing data and to explore methods to adjust for missingness. We simulated data with a continuous time‐dependent confounder and a binary treatment. We explored two classes of missing data: (i) missed visits, which resemble clinical cohort studies; (ii) missing confounder's values, which correspond to interval cohort studies. Missing data were generated under various mechanisms. In the first class, the source of the bias was the extreme treatment weights. Truncation or normalization improved estimation. Therefore, particular attention must be paid to the distribution of weights, and truncation or normalization should be applied if extreme weights are noticed. In the second case, bias was due to the misspecification of the treatment model. Last observation carried forward (LOCF), multiple imputation (MI), and inverse probability of missingness weighting (IPMW) were used to correct for the missingness. We found that alternatives, especially the IPMW method, perform better than the classic LOCF method. Nevertheless, in situations with high marker's variance and rarely recorded measurements none of the examined method adequately corrected the bias.     

Regression Models for Clinical Trials with Correlated Categorical Responses

Regression models for correlated categorical data are presented in which the covariance is a function of measured effects. The regression and covariance parameters are estimated by extended least square methods. A numerical example of a clinical trial comparing two antiemetic treatment regimes for patients receiving chemotherapy is given to illustrate the approach.