Estimating population size with truncated sampling

Let X₁, X₂,…,X_n be independent, indentically distributed random variables with density f(x,θ) with respect to a σ-finite measure μ. Let R be a measurable set in the sample space X. The value of X is observable if X ? (X?R) and not otherwise. The number J of observable X’s is binomial, N, Q, Q = 1?P(X ? R). On the basis of J observations, it is desired to estimate N and θ. Estimators considered are conditional and unconditional maximum likelihood and modified maximum likelihood using a prior weight function to modify the likelihood before maximizing. Asymptotic expansions are developed for the [Ncirc]’s of the form [Ncirc] = N + α√N + β + o_p(1), where α and β are random variables. All estimators have the same α, which has mean 0, variance σ² (a function of θ) and is asymptotically normal. Hence all are asymptotically equivalent by the usual limit distributional theory. The β’s differ and Eβ can be considered an “asymptotic bias”. Formulas are developed to compare the asymptotic biases of the various estimators. For a scale parameter family of absolutely continuous distributions with X = (0,∞) and R = (T,∞), special formuli are developed and a best estimator is found.     

Estimating with percentile grouped and truncated date from a scale parameter distribution

Data which is grouped and truncated is considered. We are given numbers n₁<…<n_k=n and we observe X_ni ),i=1,…k, and the tottal number of observations available (N> n_k is unknown. If the underlying distribution has one unknown parameter θ which enters as a scale parameter, we examine the form of the equations for both conditional, unconditional and modified maximum likelihood estimators of θ and N and examine when these estimators will be finite, and unique. We also develop expressions for asymptotic bias and search for modified estimators which minimize the maximum asymptotic bias. These results are specialized tG the zxponential distribution. Methods of computing the solutions to the likelihood equatims are also discussed.     

Range management and production on the fringe: The Caldenal, Argentina

North American problems in coming to terms with the management of the semi-arid Plains environment are well known. Less documented are those of Argentina's equivalent on the fringe of the Humid Pampas. Argentine agricultural aid and research has been focussed on the Humid Pampas, and little understanding of the special problems of the dry zone is apparent. Issues of production and conservation are in urgent need of attention. In addition to the limits posed by the natural environment, a number of human factors affect the ability of ranchers to produce from the dry lands. In a field study of the Caldenal, some indications are that the factors are different from other environments in Latin America. Large properties are not less productive per hectare than small, and standard technology does not guarantee good results from ranching. Tenant farming is not a problem, but there is an impoverished group, those ranchers without other means of earning a livelihood. A recommendation is for encouragement to be given to larger ranch units, and for more research into relevant technology, which is likely to include conservationist measures, whose introduction to the ranches should be financially supported.     

Multinomial and conditional logit discrete-choice models in demography

Although discrete-choice statistical techniques have been used with increasing regularity in demographic analyses, McFadden's conditional logit model is less well known and seldom used. Conditional logit models are appropriate when the choice among alternatives is modeled as a function of the characteristics of the alternatives, rather than (or in addition to) the characteristics of the individual making the choice. We argue that this feature of conditional logit makes it more appropriate for estimating behavioral models. In this article, the conditional logit model is presented and compared with the more familiar multinomial logit model. The difference between the two techniques is illustrated with an analysis of the choice of marital and welfare status by divorced or separated women.     

Measurement biases in user involvement research

Considerable research has been conducted to demonstrate user involvement's effect on information system success. User involvement and system success typically have been measured by asking users for their perceptions of these variables. This paper reports on a field study conducted to investigate the possibility that this approach to measuring study variables tends to overstate the benefits of user involvement. The link of user involvement to user satisfaction is found to be significantly weaker when user involvement is assessed by systems analysts than when it is self reported. Further, this difference is found to be greater for systems with few users than for systems with many users. The findings suggest that common method variance and self-serving bias may have overstated the apparent benefits of user involvement in past research on information systems. Suggestions for future research are presented.     

The Impacts of Alliance Purpose and Partner Similarity on Alliance Governance

It is generally recognized that the governance structure of an alliance has an impact on its probability of success. In this study, we examine the choice between two alternative alliance governance structures: equity and non-equity. Drawing from transaction cost economics, two sets of factors, namely alliance purpose (R&D or marketing) and cultural distance between partners, are hypothesized to influence the above choice. We further hypothesize that collaborative R&D alliances, where both parties contribute technical knowledge, are more likely to lead to the formation of equity alliances than non-collaborative research agreements, where only one partner may be doing the research work. Based on a sample of 2407 alliances formed in the global biotechnology industry, we find partial support for the hypothesized relationships. Specifically, we find that collaborative R&D alliances are more likely to be equity alliances, whereas non-collaborative R&D alliances do not have any impact on the choice of the governance form. We also find that alliances formed with a marketing purpose are less likely to be equity alliances. We did not find any relationship between cultural distance and the choice of equity alliances.     

Discussion on statistical analysis of carcinogenicity studies with an early terminated treated group

High rates of mortality on long term carcinogenicity studies can often result in challenges when it comes to the statistical analysis of tumor incidence. The current regulatory advice often results in treated groups being terminated earlier than the control group. However, this advice rarely considers the impact of this action on the statistical analyses. The nature of these analyses means that groups terminated at different times may not be directly comparable due to age differences of the animals. Here we discuss the issues related to this and investigate several approaches of how to incorporate these groups within the statistical analyses. Although no single method appears to resolve these issues consistently, inclusion of the early terminated group is still informative. Depending on the timing of the early termination, either pooling of the groups into a single terminal kill (TK) interval or reassignment of intervals based purely on time of death (ie, no separate TK interval) appear preferable. However, to draw meaningful conclusions the time of onset of a given tumor must also be considered alongside incident rates and any statistical findings.