Handling missing data by re-approaching non-respondents

When handling missing data, a researcher should be aware of the mechanism underlying the missingness. In the presence of non-randomly missing data, a model of the missing data mechanism should be included in the analyses to prevent the analyses based on the data from becoming biased. Modeling the missing data mechanism, however, is a difficult task. One way in which knowledge about the missing data mechanism may be obtained is by collecting additional data from non-respondents. In this paper the method of re-approaching respondents who did not answer all questions of a questionnaire is described. New answers were obtained from a sample of these non-respondents and the reason(s) for skipping questions was (were) probed for. The additional data resulted in a larger sample and was used to investigate the differences between respondents and non-respondents, whereas probing for the causes of missingness resulted in more knowledge about the nature of the missing data patterns

Imputation of missing network data:Some simple procedures

Analysis of social network data is often hampered by non-response and missing data. Recent studies show the negative effects of missing actors and ties on the structural properties of social networks. This means that the results of social network analyses can be severely biased if missing ties were ignored and only complete cases were analyzed. To overcome the problems created by missing data, several treatment methods are proposed in the literature: model-based methods within the framework of exponential random graph models, and im- putation methods. In this paper we focus on the latter group of methods, and investigate the use of some simple imputation procedures to handle missing network data. The results of a simulation study show that ignoring the missing data can have large negative effects on structural properties of the network. Missing data treatment based on simple imputation procedures, however, does also have large negative effects and simple imputations can only successfully correct for non-response in a few specific situations

Imputation of missing network data:Some simple procedures

Analysis of social network data is often hampered by non-response and missing data. Recent studies show the negative effects of missing actors and ties on the structural properties of social networks. This means that the results of social network analyses can be severely biased if missing ties were ignored and only complete cases were analyzed. To overcome the problems created by missing data, several treatment methods are proposed in the literature: model-based methods within the framework of exponential random graph models, and im- putation methods. In this paper we focus on the latter group of methods, and investigate the use of some simple imputation procedures to handle missing network data. The results of a simulation study show that ignoring the missing data can have large negative effects on structural properties of the network. Missing data treatment based on simple imputation procedures, however, does also have large negative effects and simple imputations can only successfully correct for non-response in a few specific situations

Palm phytoliths of mid-elevation Andean forests

Palms are one of the most common tropical plant groups. They are widespread across lowland tropical forests, but many are found in higher altitudes have more constrained environmental ranges. The limited range of these species makes them particularly useful in paleoecological and paleoclimate reconstructions. Palms produce phytoliths, or silica structures, which are found in their vegetative parts (e.g., wood, leaves, etc.). Recent research has shown that several palms in the lowland tropical forests produce phytoliths that are diagnostic to the sub-family or genus-level. Here we characterize Andean palm phytoliths, and determine whether many of these species can also be identified by their silica structures. All of our sampled Andean palm species produced phytoliths, and we were able to characterize several previously unclassified morphotypes. Some species contained unique phytoliths that did not occur in other species, particularly Ceroxylon alpinium, which is indicative of specific climatic conditions. The differences in the morphologies of the Andean species indicate that palm phytolith analysis is particularly useful in paleoecological reconstructions. Future phytolith analyses will allow researchers to track how these palm species with limited environmental ranges have migrated up and down the Andean slopes as a result of past climatic change. The phytolith analyses can track local-scale vegetation dynamics, whereas pollen, which is commonly used in paleoecological reconstructions, reflects regional-scale vegetation change

Marine benthic plants of Western Australia's shelf-edge atolls

One hundred and twenty-one species of marine algae, seagrasses and cyanobacteria are reported from the offshore atolls of northwestern Western Australia (the Rowley Shoals, Scott Reef and Seringapatam Reef). Included are 65 species of Rhodophyta, 40 species of Chlorophyta, nine species of Phaeophyceae, three species of Cyanophyta and four species of seagrasses. This report presents the first detailed account of marine benthic algae from these atolls. Twenty-four species are newly recorded for Western Australia, with four species (Anadyomene wrightii, Rhipilia nigrescens, Ceramium krameri and Zellera tawallina) also newly recorded for Australia

Delay Management with Re-Routing of Passengers

The question of delay management is whether trains should wait for a delayed feeder trainor should depart on time. In classical delay management models passengers always taketheir originally planned route. In this paper, we propose a model where re-routing ofpassengers is incorporated.To describe the problem we represent it as an event-activity network similar to the oneused in classical delay management, with some additional events to incorporate originand destination of the passengers. We present an integer programming formulation ofthis problem. Furthermore, we discuss the variant in which we assume fixed costs formaintaining connections and we present a polynomial algorithm for the special case ofonly one origin-destination pair. Finally, computational experiments based on real-worlddata from Netherlands Railways show that significant improvements can be obtained bytaking the re-routing of passengers into account in the model.public transportation;OD-pairs;delay management;re-routing

Combining Column Generation and Lagrangian Relaxation

Although the possibility to combine column generation and Lagrangian relaxation has been known for quite some time, it has only recently been exploited in algorithms. In this paper, we discuss ways of combining these techniques. We focus on solving the LP relaxation of the Dantzig-Wolfe master problem. In a first approach we apply Lagrangian relaxation directly to this extended formulation, i.e. no simplex method is used. In a second one, we use Lagrangian relaxation to generate new columns, that is Lagrangian relaxation is applied to the compact for-mulation. We will illustrate the ideas behind these algorithms with an application in Lot-sizing. To show the wide applicability of these techniques, we also discuss applications in integrated vehicle and crew scheduling, plant location and cutting stock problems.column generation;Lagrangean relaxation;cutting stock problem;lotsizing;vehicle and crew scheduling