Comment: Struggles with Survey Weighting and Regression Modeling

Comment: Struggles with Survey Weighting and Regression Modeling [arXiv:0710.5005]Comment: Published in at http://dx.doi.org/10.1214/088342307000000186 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

The Likelihood of a Continuous-time Vector Autoregressive Model

This paper provides a method that weakens conditions under which the exact likelihood of a continuous-time vector autoregressive model can be derived. In particular, the method does not require the restrictions extant methods impose on discrete data that limit the applicability of continuous-time methods to real economic time series. The method applies generally to higher-order continuous-time systems involving mixed stock and flow data.Continuous-time, Vector autoregression, Exact likelihood, Time series

Block-Conditional Missing at Random Models for Missing Data

Two major ideas in the analysis of missing data are (a) the EM algorithm [Dempster, Laird and Rubin, J. Roy. Statist. Soc. Ser. B 39 (1977) 1--38] for maximum likelihood (ML) estimation, and (b) the formulation of models for the joint distribution of the data ${Z}$ and missing data indicators ${M}$, and associated "missing at random"; (MAR) condition under which a model for ${M}$ is unnecessary [Rubin, Biometrika 63 (1976) 581--592]. Most previous work has treated ${Z}$ and ${M}$ as single blocks, yielding selection or pattern-mixture models depending on how their joint distribution is factorized. This paper explores "block-sequential"; models that interleave subsets of the variables and their missing data indicators, and then make parameter restrictions based on assumptions in each block. These include models that are not MAR. We examine a subclass of block-sequential models we call block-conditional MAR (BCMAR) models, and an associated block-monotone reduced likelihood strategy that typically yields consistent estimates by selectively discarding some data. Alternatively, full ML estimation can often be achieved via the EM algorithm. We examine in some detail BCMAR models for the case of two multinomially distributed categorical variables, and a two block structure where the first block is categorical and the second block arises from a (possibly multivariate) exponential family distribution.Comment: Published in at http://dx.doi.org/10.1214/10-STS344 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

The role of Skorokhod space in the development of the econometric analysis of time series

This paper discusses the fundamental role played by Skorokhod space, through its underpinning of functional central limit theory, in the development of the paradigm of unit roots and co-integration. This paradigm has fundamentally affected the way economists approach economic time series as was recognized by the award of the Nobel Memorial Prize in Economic Sciences to Robert F. Engle and Clive W.J. Granger in 2003. Here, we focus on how P.C.B. Phillips and others used the Skorokhod topology to establish a limiting distribution theory that underpinned and facilitated the development of methods of estimation and testing of single equations and systems of equations with possibly integrated regressors. This approach has spawned a large body of work that can be traced back to Skorokhod's conception of fifty years ago. Much of this work is surprisingly confined to the econometrics literature.Skorokhod space, functional central limit theorems, non-stationary time series, unit roots and co-integration, Wiener functionals, econometrics.

Examination of the impact and effectiveness of herd health and welfare assessment in im-proving animal welfare on organic dairy farms, using qualitative interviews.

During winter 2002-03, 15 organic dairy farms in SW England participated in a herd health and welfare assessment and benchmarking study. A second assessment was carried out on 14 of the original 15 farms and on 14 new farms during winter 2003-04. The effectiveness of the herd health and welfare as-sessments and benchmarking in delivering animal health and welfare improvements was investigated by means of qualitative research interviews. The inter-views were conducted between August and November 2004. The average length of interview was one hour and fifteen minutes. Five common themes were iden-tified and headed ‘Sensitivities and misgivings’; ‘Ac-ceptability of scoring methodology and indicators assessed’; ‘Raised awareness and motivation to im-prove’; ‘Veterinary support and herd health planning’ and ‘Value of assessment and benchmarking’. It was apparent that farmers, who took part voluntarily in the study, took the results of the herd health and welfare assessments very seriously and were clearly motivated by the process. The main focus for change was related to housing issues. The main constraints to welfare improvement were a shortage of finance to affect change beyond relatively simple alterations and a lack of information on the identification of changes likely to improve animal welfare in given situations

Effects of Portfolio Planning Methods on Decision Making: Experimental Results*

Subjects (n = 1015) working individually in the role of managers were asked to choose between investment opportunities that would either double their investment or cause the loss of half of it. Six administrators ran experiments on 27 occasions in six countries over a five-year period. Information about the BCG matrix increased the subjects' likelihood of selecting the project that was clearly less profitable. Of subjects exposed to the BCG matrix, 64% selected the unprofitable investment. Of subjects who used the BCG matrix in their analysis, 87% selected the less profitable investment.decision making, marketing, portfolio planning methods

Portfolio Planning Methods: Faulty Approach or Faulty Research? A Rejoinder to 'Making Better Decisions' by Wensley

Wensley (1994) makes three key points. First, it is worthwhile to conduct empirical studies of the value of management techniques. Second, managers probably misuse portfolio methods. Third, the Armstrong and Brodie study is flawed. We agree with all three points.marketing, portfolio planning methods

Hypotheses in Marketing Science: Literature Review and Publication Audit

We examined three approaches to research in marketing: exploratory hypotheses, dominant hypothesis, and competing hypotheses. Our review of empirical studies on scientific methodology suggests that the use of a single dominant hypothesis lacks objectivity relative to the use of exploratory and competing hypotheses approaches. We then conducted a publication audit of over 1,700 empirical papers in six leading marketing journals during 1984-1999. Of these, 74% used the dominant hypothesis approach, while 13 % used multiple competing hypotheses, and 13% were exploratory. Competing hypotheses were more commonly used for studying methods (25%) than models (17%) and phenomena (7%). Changes in the approach to hypotheses since 1984 have been modest; there was a slight decrease in the percentage of competing hypotheses to 11%, which is plained primarily by an increasing proportion of papers on phenomena. Of the studies based on hypothesis testing, only 11 % described the conditions under which the hypotheses would apply, and dominant hypotheses were below competing hypotheses in this regard. Marketing scientists differed substantially in their opinions about what types of studies should be published and what was published. On average, they did not think dominant hypotheses should be used as often as they were, and they underestimated their use