Investigating call record data using sequence analysis to inform adaptive survey designs

Researchers have become increasingly interested in better understanding the survey data collection process in interviewer-administered surveys. However, tools for analysing paradata capturing information about field processes, also called call record data, are still not yet fully explored. This paper introduces sequence analysis as a simple tool for investigating such data with the aim of better understanding and improving survey processes. A novel approach is to use sequence analysis within interviewers, which allows the identification of unusual interviewer calling behaviours, and may provide guidance on interviewer performance. Combining the technique with clustering, optimal matching and multidimensional scaling, the method offers a way of visualising, displaying and summarising complex call record data. The method is introduced to inform survey management and survey monitoring. The method is hence informative for adaptive survey designs and will help to identify unusual behaviour and outliers and to improve survey processes. Sequence analysis is applied to call record data from the UK Understanding Society survey. The findings inform further modelling of call record data to increase efficiency in call scheduling.     

On the equivalence of definitions for regular fractions of mixed-level factorial designs

The notion of regularity for fractional factorial designs was originally defined only for two-level factorial designs. Recently, rather different definitions for regular fractions of mixed-level factorial designs have been proposed by Collombier [1996. Plans d’Expérience Factoriels. Springer, Berlin], Wu and Hamada [2000. Experiments. Wiley, New York] and Pistone and Rogantin [2008. Indicator function and complex coding for mixed fractional factorial designs. J. Statist. Plann. Inference 138, 787–802]. In this paper we prove that, surprisingly, these definitions are equivalent. The proof of equivalence relies heavily on the character theory of finite Abelian groups. The group-theoretic framework provides a unified approach to deal with mixed-level factorial designs and treat symmetric factorial designs as a special case. We show how within this framework each regular fraction is uniquely characterized by a defining relation as for two-level factorial designs. The framework also allows us to extend the result that every regular fraction is an orthogonal array of a strength that is related to its resolution, as stated in Dey and Mukerjee [1999. Fractional Factorial Plans. Wiley, New York] to mixed-level factorial designs.     

Immediate Effects of a 16-Week Life Skills Education Program on the Mental Health of Adult Psychiatric Patients

ABSTRACT

A total of 206 (105 men, 101 women) adult psychiatric patients participated in life skills programming 5 half days per week for 16 weeks. Psychosocial adjustment was assessed pre- and post-treatment with the three primary scales of the Holden Psychological Screening Inventory (HPSI). A multivariate pre- versus post-treatment analysis resulted in a nonsignificant effect for the covariate age (p= .136) but significant effects for time (p<.0005), gender (p<.0005), and the time by gender interaction (p= .003). Depression Symptomatology improved significantly for both men and women, whereas on the other two HPSI scales (Psychiatric and Social Symptomatology) statistically significant improvements were only obtained for women. The Social Symptomatology effect size for women (.25) was small and of the same order of magnitude as a treatment as usual psychiatric patient control sample and is therefore primarily a retesting effect. The effect sizes for Depression Symptomatology for men and women (.77 and .87, respectively) and Psychiatric Symptomatology for women (.57) were large and at least four times larger than the control sample. Improvement in Depression Symptomatology has considerable support in the literature but improvement in Psychiatric Symptomatology does not and will therefore require replication.     

Three Parallel Flats Designs for Two-level Factorial Experiments

This paper investigates the properties of the class of three parallel flats designs for two-level factorial experiments. It shows that the designs constructed from this class of designs can have a very simple correlation structure. The correlation of any pair of best linear unbiased estimators of factorial effects is 0, ⅓ or ¼. Furthermore, the designs obtained also have high D-efficiency. Finally, a class of designs is generated with run-size N = 12 to illustrate the use of the theorem.     

Book Reviews

Books reviewed:
Robert E., Kass and Paul W., Vos, Geometrical Foundations of Asymptotic Inference: Curved Exponential Families
G.S., Maddala and C.R., Rao, (eds) Handbook of Statistics 15: Robust Inference
Gregory C., Reinsel, Elements of Multivariate Time Series Analysis
Murray, Rosenblatt, Gaussian and Non-Gaussian Linear Time Series and Random Fields
William S., Mallios, The Analysis of Sports Forecasting: Modeling Parallels Between Sports Gambling and Financial Markets
Alain, Desrosières, The Politics of Large Numbers — A History of Statistical Reasoning
Mahmut, Parlar, Interactive Operations Research with MAPLE Methods and Models     

Model Discrimination Criteria on Model-Robust Designs

Recently, interest about model discrimination has been focused on methods based on model estimation. Due to the problem of model aliasing, several criteria have been proposed aimed at assessing the capacity of a design for model discrimination. Three of these measures, along with a new criterion that combines them and assesses the overall discrimination capacity of a design, are implemented to evaluate a class of 27-run orthogonal arrays in three levels.     

The plan of enrichment designs for dealing with high placebo response

To deal with high placebo response in clinical trials for psychiatric and other diseases, different enrichment designs, such as the sequential parallel design, two‐way enriched design, and sequential enriched design, have been proposed and implemented recently. Depending on the historical trial information and the trial sponsors' resources, detailed design elements are needed for determining which design to adopt. To assist in making more suitable decisions, we perform evaluations for selecting required design elements in terms of power optimization and sample size planning. We also discuss the implementation of the interim analysis related to its applicability.     

Projection designs for mixture experiments in orthogonal blocks

Mixture experiments are often carried out in the presence of process variables, such as days of the week or different machines in a manufacturing process, or different ovens in bread and cake making. In such experiments it is particularly useful to be able to arrange the design in orthogonal blocks, so that the model in tue mixture vanauies may ue iitteu inucpenuentiy or tne UIOCK enects mtrouuceu to take account of the changes in the process variables. It is possible in some situations that some of the ingredients in the mixture, such as additives or flavourings, are present in soian quantities, pernaps as iuw a.s 5% ur even !%, resulting in the design space being restricted to only part of the mixture simplex. Hau and Box (1990) discussed the construction of experimental designs for situations where constraints are placed on the design variables. They considered projecting standard response surface designs, including factorial designs and central composite designs, into the restricted design space, and showed that the desirable property of block orthogonality is preserved by the projections considered. Here we present a number of examples of projection designs and illustrate their use when some of the ingredients are restricted to small values, such that the design space is restricted to a sub-region within the usual simplex in the mixture variables.     

N the theory of randomized responses to two sensitive questions

This paper sets forth a stochastic model which can be applied to randomized response designs wherein more than one question is sensitive of stigmatizing. Using three specific designs applied to a pair of stigmatizing or sensitive traits leading to two by two contingency tables, it is proved that if the two traits are statistically independent then the responses are also and conversely. The converse statement gives the support we need for inference to be made on the traits based on the randomized responses.