Modeling social networks from sampled data

Network models are widely used to represent relational information among interacting units and the structural implications of these relations. Recently, social network studies have focused a great deal of attention on random graph models of networks whose nodes represent individual social actors and whose edges represent a specified relationship between the actors. Most inference for social network models assumes that the presence or absence of all possible links is observed, that the information is completely reliable, and that there are no measurement (e.g., recording) errors. This is clearly not true in practice, as much network data is collected though sample surveys. In addition even if a census of a population is attempted, individuals and links between individuals are missed (i.e., do not appear in the recorded data). In this paper we develop the conceptual and computational theory for inference based on sampled network information. We first review forms of network sampling designs used in practice. We consider inference from the likelihood framework, and develop a typology of network data that reflects their treatment within this frame. We then develop inference for social network models based on information from adaptive network designs. We motivate and illustrate these ideas by analyzing the effect of link-tracing sampling designs on a collaboration network.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS221 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

On the Concept of Snowball Sampling

This brief comment reflects on the historical and current uses of the term "snowball sampling."Comment: 5 pages, 0 figures. To appear in Sociological Methodolog

Respondent-Driven Sampling: An Assessment of Current Methodology

Respondent-Driven Sampling (RDS) employs a variant of a link-tracing network sampling strategy to collect data from hard-to-reach populations. By tracing the links in the underlying social network, the process exploits the social structure to expand the sample and reduce its dependence on the initial (convenience) sample. The primary goal of RDS is typically to estimate population averages in the hard-to-reach population. The current estimates make strong assumptions in order to treat the data as a probability sample. In particular, we evaluate three critical sensitivities of the estimators: to bias induced by the initial sample, to uncontrollable features of respondent behavior, and to the without-replacement structure of sampling. This paper sounds a cautionary note for the users of RDS. While current RDS methodology is powerful and clever, the favorable statistical properties claimed for the current estimates are shown to be heavily dependent on often unrealistic assumptions.Comment: 35 pages, 29 figures, under revie

Attraction of Aerial Insects as a Fish Food Supplement

Insect populations over a 1.2 hectare southeast Arkansas livestock pond were sampled to consider the possibility of their use as a fish food supplement. A commercial insect attraction unit was suspended above the pond, and attracted insects were collected. Insect populations were sampled 3-4 nights each month, January-December, 1976. Insects collected were identified and analyses were performed to determine nutritional composition and pesticide content. Insect samples were variable, however, 62% of the insects identified were in the Order Diptera and 97% of these were in the Family Chironomidae. Nutritional analyses revealed insects were more than 60% crude protein. Pesticide analysis indicated 0.98 ppm toxaphene was present in the insect

Mosquitofish, Gambusia affinis (Baird and Girard) Production in Extensive Polyculture System

During 1976, mosquitofish, Gambusia affinis Baird and Girard, were reared in combination with food and game fishes in 0.1 ha culture ponds at the University of Arkansas at Pine Bluff fisheries research facility. Mosquitofish production was 218 kg/ha, with 1683 fish per kilogram, in ponds that were also stocked with channel catfish, Ictalurus punctatus Rafinesque, bigmouth buffalo, Ictiobus cyprinellus Valenciennes, grass carp, Ctenopharyngodon idella Valenciennes, and silver carp, Hypophthalmichthys molitrix Valenciennes. In another similar stocked pond, hybrid sunfish fingerlings depressed mosquitofish yield by 79%. No mosquitofish production was obtained in ponds stocked with 250 largemouth bass, Xficropterus salmoides Lacepede, fry per hectare, although fathead minnows, Pimephales promelas Rafinesque, were added to buffer mosquitofish predation. Total fish yields ranged from 414 to 670 kg/ha for the polyculture systems investigated

Condition numbers and scale free graphs

In this work we study the condition number of the least square matrix corresponding to scale free networks. We compute a theoretical lower bound of the condition number which proves that they are ill conditioned. Also, we analyze several matrices from networks generated with the linear preferential attachment model showing that it is very difficult to compute the power law exponent by the least square method due to the severe lost of accuracy expected from the corresponding condition numbers.Comment: Submitted to EP

Opportunities for Improving Livestock Production with e-Management Systems

There is increased interest in hardware and software that can support e-Management for grassland-based livestock industries. Managers of grazing livestock were early adopters of radio frequency identification (RFID) technologies automatically monitoring individual animal performance. Recent developments of remote sensing, automated individual recording and management, location based systems, improved data transfer and technologies that can be used in more extensive grazing systems are providing new opportunities for the development of e-Management systems. There is a need for better data integration and systems that can provide the best available information to enable better decision-making. For greater industry adoption of more integrated e-Management systems, there needs to be a clear economic value. With increased on farm monitoring and the expansion of digital data sources, grazing livestock production systems have the opportunity to expand production efficiency through the implementation of e-Management

Effect of farm system and milk urea phenotype on milk yield and milk composition of dairy cows in Canterbury

To investigate the effect of farm system, and cow selection for milk urea nitrogen (MUN), on milk yield and milk composition, a farmlet study was carried out between October 2018 and May 2019 in Lincoln, Canterbury. A farm system with a low stocking rate and low N fertiliser input (LSR, 2.9 cows/ha) sown with a conventional ryegrass clover and plantain diverse pastures was compared with a farm system with a moderate stocking rate and moderate N fertiliser (MSR, 3.9 cows/ha) using conventional ryegrass and white clover pastures and supplementing 3 kg DM/cow/d as crushed barley grain. Each farmlet had total herd size of 40 mixed-age HF x J spring-calving dairy cows which included six cows selected solely for a high MUN or a low MUN. There was no effect of farm system on milk fat, protein or lactose content but MUN was lower in LSR compared with MSR. Milk production was also lower for LSR (466 vs 429±12.4 kg MS/cow/ha, P<0.05), owing to poorer quality diet in mid lactation. Cows selected for low MUN tended to produce less milk compared with high MUN cows (4478 vs 3987±174 kg/cow, P<0.10) though this was partially offset by increased protein content in milk of low MUN cows. Farm system and animal selection for MUN have a greater impact on milk yield than on milk composition