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The statistical problems of intercropping experiments (which involve the growing of two or more crops together) are investigated in this study. Measures of combined yield are discussed; the Land Equivalent Ratio (LER) is shown to be the 'best' index for intercropping. Problems that arise in the standardization of LER are investigated, and use of a single pair of divisors is recommended. The use of systematic designs are advocated for yield-density studies, to reduce the number of guard rows. A 3-way systematic design is proposed and methods of analysis are suggested. A regression model is employed for the combined yield data (LER), from which estimates of the optimum densities can be calculated. The study also deals with varietal trials in intercropping. Methods for reducing the large number of possible varietal combinations to be tested in the field and ways of reducing the block size are given. The field layout is discussed, and illustrated by examples. Stability measures that can be used in intercropping are derived and it is shown how they can be used in evaluating stable varietal combinations. It is also shown how information about the contribution to stability of each crop can be obtained. The best proportions of the component crops in the intercropping mixture is also investigated. Design and analysis for an experiment on proportions in conjunction with varying densities is given. / Ph. D. / incomplete_metadata

Two prominent monitoring procedures in statistical quality control are the p-chart for the proportion of items defective, and the c-chart, for the number of defects per item. These procedures are reconsidered, and some extensions are examined for monitoring processes with multiple attributes. Some relevant distribution theory is reviewed, and some new results are given. The distributions considered are multivariate versions of the binomial, Poisson, and chi-squared distributions, plus univariate and multivariate generalized Poisson distributions. All of these distributions prove useful in the discussion of attribute control charts. When quality standards are known, p-charts and c-charts are shown to have certain optimal properties. Generalized p-charts, for monitoring multinomial processes, and generalized c-charts are introduced. Their properties are shown to depend upon multivariate chi-squared and generalized Poisson distributions, respectively. Various techniques are considered for monitoring multivariate Bernoulli, Poisson, multinomial, and generalized Poisson processes. Omnibus procedures are given, and some of their asymptotic properties are derived. Also examined are diagnostic procedures based upon both small- and large-sample. / Ph. D.

Deterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study evaluates the efficacy of traditional interpolation methods for estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky are used as a case study, and several error and performance measures are used to evaluate the trade-offs in accuracy of estimation and preservation of site and regional statistics. / by Husayn El Sharif. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Objective. The Cochrane risk of bias tool (CRoB) is one of the most widely used tools for assessing the risk of bias of clinical trials. However, it was criticized for its poor inter-rater reliability, lack of clear and detailed guidelines for its application, and no clear distinguishing between reporting quality from real quality in implementation. This study aims to develop a framework (or improved CRoB, iCRoB) so as to improve the inter-rater reliability of the CRoB in its first 4 domains: sequence generation, allocation concealment, blinding of participants and personnel, and blinding of outcome assessment, through providing: i) a structured pathway for assessing risk of bias assessment; and ii) a comprehensive dictionary of scenarios for each domain. / Methods. The study is consisted of 4 steps: / i) Step 1: Develop a step-by-step structured pathway for assessing the risk of bias. / ii) Step 2: Identify and summarize possible scenarios that are used in literature to describe a domain in clinical trials by using a qualitative content analysis approach. A random sample of 100 Cochrane systematic reviews (SRs) was taken from the Cochrane Database of Systematic Reviews. Each review was carefully scrutinized for this purpose. / iii) Step 3: Merge the scenarios identified from the sample with those already provided in the CRoB. The combined list of scenarios extends the current coverage of the CRoB and forms a more comprehensive dictionary of scenarios for use in the future. The bias assessment pathway and the new dictionary of scenarios in combination are the new components added or contribution to the CRoB to form the iCRoB. / v) Step 4: Conduct a randomized controlled study that allocated at random 8 raters equally into either using the CRoB or our new iCRoB. 150 clinical trials were randomly selected from the fore-mentioned 100 SRs for the inter-rater reliability comparison. Both inter-rater reliability among individual raters (measured with Fleiss’ κ) and that across rater pairs (measured with weighted Cohen’s κ) were computed. Data analyses were conducted by using STATA version 13.0. / Results. A structured pathway for systematically assessing bias was designed, which helps classify a study into one of 5 categories for each risk of bias domain based on the information provided in the report of a trial: Category A: a trial reports in details how a bias reduction method was conducted and it is also deemed by the assessor to be conducted adequately; Category B: a trial reports in details how a bias reduction method was conducted but it is deemed by the assessor to be conducted inadequately; Category C: a trial reports that a bias reduction method was conducted but no detailed description was given which can be used to judge whether it was done adequately; Category D: a trial reports that a bias reduction method was not conducted; Category E: a trial does not mention at all whether or not a bias reduction method was conducted. / A total of 34, 36, 26 and 20 scenarios were generated for sequence generation, allocation concealment, blinding of participants and personnel, and blinding of outcome assessment, respectively. We extended the current CRoB list of scenarios by a number of 20, 23, 26 and 20 respectively for the 4 bias reduction domains. / Our trial results showed that the iCRoB had a higher inter-rater reliability across rater pairs than the original CRoB for every bias reduction domain. The weighted κ was 0.71 and 0.81 for sequence generation respectively for CRoB and iCRoB; 0.53 and 0.61 for allocation concealment respectively for CRoB and iCRoB; 0.56 for blinding of participants and personnel in CRoB, 0.68 for blinding of participants and 0.70 for blinding of personnel ini CRoB; and 0.19 and 0.43 for blinding of outcome assessment respectively for CRoB and iCRoB. / Conclusion. We developed the iCRoB including a standard pathway and extended substantively the dictionary of scenarios for making the judgement on risk of bias in the reports of clinical trials. Our iCRoB showed a higher reliability than the current CRoB in all the domains examined. The iCRoB can be recommended for improving the assessment of bias in clinical trials. / 目的：考柯藍偏倚風險評估工具(CRoB)是最廣泛應用的用於評價臨床試驗偏倚風險的工具之一。然而，CRoB 有以下三個缺陷：評價者間信度低，缺乏明確和詳細的應用說明和沒有明確區分報告質量和方法學質量。本研究擬制定一個新的工具iCRoB 用以提高CRoB 前4 項指標的評價者間信度。這4項指標分別為隨機序列生成，分配隱藏，對研究對象和研究者實施盲法，和對結局評估者實施盲法。本研究通過以下2 點實現這一目的：i) 提供一個結構化路徑用以評估偏倚風險；ii) 為每個研究指標提供一個廣泛包含偏倚風險評估相關描述場景的字典。 / 方法：本研究包含以下4 個步驟： / 第1 步：制定一個用以評估偏倚風險的結構化路徑。 / 第2 步：從考柯藍系統綜述數據庫中隨機抽取100 篇系統綜述，應用定性內容分析法從中確定並總結出臨床試驗中與偏倚風險相關的可能的描述場景。 / 第3 步：將從100 個樣本中總結的描述場景與CRoB 中已有的場景合併，從而擴大CRoB 的描述場景的覆蓋範圍，得到一個更廣泛包含偏倚風險評估相關描述場景字典。偏倚風險評估的結構化路徑和包含場景描述的字典共同形成了本研究中新制定的iCRoB，用以評估臨床試驗的偏倚風險。 / 第4 步：在一個隨機對照研究中，8 名評價者被隨機平均分配至CRoB 組或者iCRoB 組。在上述100個系統綜述所納入的臨床試驗中隨機抽取150 個臨床試驗用以比較CRoB 和iCRoB 的評價者間信度。評價者間信度的比較包括個體評價者間信度（用Fleiss’κ 測量）和配對評價者間信度(用加權Cohen’s κ 測量)的比較。數據採用Stata 13.0 進行統計分析。 / 結果：本研究成功的制定了一個用於系統評價偏倚風險的結構化路徑，在該結構化路徑中，每個偏倚風險相關的指標在一個臨床研究中將分為以下5 類： / A 類：臨床試驗詳細描述了預防偏倚的措施的實施，根據描述可以判定該措施的實施能預防偏倚的產生; B 類：臨床試驗詳細描述了預防偏倚的措施的實施，根據描述可以判定該措施的實施不能預防偏倚的產生; C 類：臨床試驗報告採取了預防偏倚的措施，但未描述這一過程如何實施，從而無法判斷其實施是否正確; D 類：臨床試驗報告沒有採取任何預防偏倚的措施; E 類：臨床試驗沒有報告是否採取了預防偏倚的措施。 / 本研究分別為隨機序列生成，分配隱藏，對研究對象和研究者實施盲法，和對結局評估者實施盲法收集了34，36，26 和20 個描述場景。與CRoB 提供的描述場景比較，iCRoB 分別為隨機序列生成，分配隱藏，對研究對象和研究者實施盲法，和對結局評估者實施盲法增加了20，23，26 和20 個新的描述場景。 / 隨機對照試驗結果顯示，iCRoB 中每個研究指標的配對評價者間信度均高於CRoB，其中，隨機序列生成加權κ 為0.71（CRoB）和0.81（iCRoB），分配隱藏加權κ 為0.53（CRoB）和0.61（iCRoB），對研究對象和研究者實施盲法加權κ 為0.56（CRoB），對研究對象實施盲法加權κ 為0.68（iCRoB），對研究者實施盲法加權κ 為0.70（iCRoB），對結局評估者實施盲法加權κ 為0.19（CRoB）和0.43（iCRoB）。 / 結論：本研究通過制定一個由偏倚風險評估的結構化路徑和包含場景描述的字典組成的iCRoB，用以改善CRoB 中對臨床試驗中隨機序列生成，分配隱藏，對研究對象和研究者實施盲法，和對結局評估者實施盲法偏倚風險評估過程。相比於CRoB，iCRoB 在每個研究指標中均顯示出更好的配對評價者間信度。這些結果證明評價者間信度可以通過提供結構化偏倚風險評估路徑和更全面的描述場景字典而提高。 / Wu, Xinyin. / Thesis Ph.D. Chinese University of Hong Kong 2014. / Includes bibliographical references (leaves 93-105). / Abstracts also in Chinese. / Title from PDF title page (viewed on 09, September, 2016). / Wu, Xinyin. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.y066 / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

Finite mixture modeling is a useful statistical technique for clustering individuals based on patterns of responses. The fundamental idea of the mixture modeling approach is to assume there are latent clusters of individuals in the population which each generate their own distinct distribution of observations (multivariate or univariate) which are then mixed up together in the full population. Hence, the name mixture comes from the fact that what we observe is a mixture of distributions. The goal of this model-based clustering technique is to identify what the mixture of distributions is so that, given a particular response pattern, individuals can be clustered accordingly. Commonly, finite mixture models, as well as the special case of latent class analysis, are used on data that inherently involve repeated measures. The purpose of this dissertation is to extend the finite mixture model to allow for the number of repeated measures to be incorporated and contribute to the clustering of individuals rather than measures. The dimension of the repeated measures or simply the count of responses is assumed to follow a truncated Poisson distribution and this information can be incorporated into what we call a dimension informative finite mixture model (DIMM). The outline of this dissertation is as follows. Paper 1 is entitled, "Dimension Informative Mixture Modeling (DIMM) for questionnaire data with an informative number of repeated measures." This paper describes the type of data structures considered and introduces the dimension informative mixture model (DIMM). A simulation study is performed to examine how well the DIMM fits the known specified truth. In the first scenario, we specify a mixture of three univariate normal distributions with different means and similar variances with different and similar counts of repeated measurements. We found that the DIMM predicts the true underlying class membership better than the traditional finite mixture model using a predicted value metric score. In the second scenario, we specify a mixture of two univariate normal distributions with the same means and variances with different and similar counts of repeated measurements. We found that that the count-informative finite mixture model predicts the truth much better than the non-informative finite mixture model. Paper 2 is entitled, "Patterns of Physical Activity in the Northern Manhattan Study (NOMAS) Using Multivariate Finite Mixture Modeling (MFMM)." This is a study that applies a multivariate finite mixture modeling approach to examining and elucidating underlying latent clusters of different physical activity profiles based on four dimensions: total frequency of activities, average duration per activity, total energy expenditure and the total count of the number of different activities conducted. We found a five cluster solution to describe the complex patterns of physical activity levels, as measured by fifteen different physical activity items, among a US based elderly cohort. Adding in a class of individuals who were not doing any physical activity, the labels of these six clusters are: no exercise, very inactive, somewhat inactive, slightly under guidelines, meet guidelines and above guidelines. This methodology improves upon previous work which utilized only the total metabolic equivalent (a proxy of energy expenditure) to classify individuals into inactive, active and highly active. Paper 3 is entitled, "Complex Drug Use Patterns and Associated HIV Transmission Risk Behaviors in an Internet Sample of US Men Who Have Sex With Men." This is a study that applies the count-informative information into a latent class analysis on nineteen binary drug items of drugs consumed within the past year before a sexual encounter. In addition to the individual drugs used, the mixture model incorporated a count of the total number of drugs used. We found a six class solution: low drug use, some recreational drug use, nitrite inhalants (poppers) with prescription erectile dysfunction (ED) drug use, poppers with prescription/non-prescription ED drug use and high polydrug use. Compared to participants in the low drug use class, participants in the highest drug use class were 5.5 times more likely to report unprotected anal intercourse (UAI) in their last sexual encounter and approximately 4 times more likely to report a new sexually transmitted infection (STI) in the past year. Younger men were also less likely to report UAI than older men but more likely to report an STI.

This dissertation presents an historical-sociological study of how governments of the modern western state use the language and techniques of quantification in the domain of social policy. The case material has an Australian focus. The thesis argues that by relying on techniques of quantification, governments risk introducing a false legitimacy to their social policy decisions. The thesis takes observed historical phenomena, language and techniques of quantification for signifying the social, and seeks meaningful interpretations in light of the culturally embedded actions of individuals and collective members of Australian bureaucracies. These interpretations are framed by the arguments of a range of scholars on the sociology of mathematics and quantitative technologies. The interpretative framework is in turn grounded in the history and sociology of modernity since the Enlightenment period, with a particular focus on three aspects: the nature and purpose of the administrative bureaucracy, the role of positivism in shaping scientific inquiry and the emergence of a risk consciousness in the late twentieth century. The thesis claim is examined across three case studies, each representative of Australian government action in formulating social policy or providing human services. Key social entities examined include the national census of population, housing needs indicators, welfare program performance and social capital. The analysis of these social statistics reveals a set of recurring characteristics that are shown to reduce their certainty. The analysis provides evidence for a common set of institutional attitudes toward social numbers, essentially that quantification is an objective technical device capable of reducing unstable social entities to stable, reliable significations (numbers). While this appears to strengthen the apparatus of governmentality for developing and implementing state policy, ignoring the many unarticulated and arbitrary judgments that are embedded in social numbers introduces a false legitimacy to these government actions.

This thesis concerns the development, estimation and investigation of a general anisotropic spatial correlation function, within model-based geostatistics, expressed as a Gaussian linear mixed model, and estimated using residual maximum likelihood (REML). The Matern correlation function is attractive because of its parameter which controls smoothness of the spatial process, and which can be estimated from the data. This function is combined with geometric anisotropy, with an extension permitting different distance metrics, forming a flexible spatial covariance model which incorporates as special cases many infinite- range spatial covariance functions in common use. Derivatives of the residual log-likelihood with respect to the four correlation-model parameters are derived, and the REML algorithm coded in Splus for testing and refinement as a precursor to its implementation into the software ASReml, with additional generality of linear mixed models. Suggestions are given regarding initial values for the estimation. A residual likelihood ratio test for anisotropy is also developed and investigated. Application to three soil-based examples reveals that anisotropy does occur in practice, and that this technique is able to fit covariance models previously unavailable or inaccessible. Simulations of isotropic and anisotropic data with and without a nugget effect reveal the following principal points. Inclusion of some closely-spaced locations greatly improves estimation, particularly of the Matern smoothness parameter, and of the nugget variance when present. The presence of geometric anisotropy does not adversely affect parameter estimation. Presence of a nugget effect introduces greater uncertainty into the parameter estimates, most dramatically for the smoothness parameter, and also increases the chance of non-convergence and decreases the power of the test for anisotropy. Estimation is more difficult with very “unsmooth" processes (Matern smoothness parameter 0.1 or 0.25) | non- convergence is more likely and estimates are less precise and/or more biased. However it is still often possible to fit the full model including both anisotropy and nugget effect using REML with as few as 100 observations. Additional simulations involving model misspecification reveal that ignoring anisotropy when it is present can substantially increase the mean squared error of prediction, but overfitting by attempting to model anisotropy when it is absent is less damaging. Further, plug-in estimates of prediction error variance are reasonable estimates of the actual mean squared error of prediction, regardless of the model fitted, weakening the argument requiring Bayesian approaches to properly allow for uncertainty in the parameter estimates when estimating prediction error variance. The most valuable outcome of this research is the implementation of an anisotropic Matern correlation function in ASReml, including the full generality of Gaussian linear mixed models which permits additional fixed and random effects, making publicly available the facility to fit, via REML estimation, a much wider range of variance models than has previously been readily accessible. This greatly increases the probability and ease with which a well-fitting covariance model can be found for a spatial data set, thus contributing to improved geostatistical spatial analysis. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1297562 / Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 2007

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