关注"常态"生活的意义——家庭社会学研究的一个新视角初探

本文从日常生活的"常态"概念入手,认为选择这样一个"常态"作为研究对象对研究家庭社会学是十分有意义的.具体地说,我们认为以被访人的生活史为切入点,去挖掘和揭示制度安排中的"盲点",应该成为家庭社会学研究的一个新的视角.     

Conflicting contexts: Midwives’ interpretation of childbirth through photo elicitation

IntroductionThis study seeks to explore midwives’ perceptions about childbirth and in particular their beliefs about normality and risk. In the current climate of increasing interventions during labour, it is important to understand the thought processes that impact on midwifery care in order to examine whether these beliefs influence midwifery clinical decision-making.Method12 Midwives who worked in a variety of metropolitan hospitals in Sydney, Australia were interviewed about how they care for women during labour. The study utilised an inductive qualitative design using photo elicitation during the interview process.ResultsSix themes emerged from the data that clearly indicated midwives felt challenged by working in a system dominated by an obstetric model of care that undermined midwifery autonomy in maintaining normal birth. These themes were: desiring normal, scanning the environment, constructing the context, navigating the way, relinquishing desire and reflecting on reality. Most midwives felt they were unable to practice in the manner they were philosophically aligned to, that is, promoting normal birth, as the medical model restricted their practice.DiscussionThe polarised views of childbirth held by midwives and obstetricians do little to enhance normal birth outcomes. Midwives in this study expressed frustration that they were unable to practice midwifery in a way that reflected their belief in normal birth. This, they cite is a result of the oppressive obstetric model prevalent in maternity care facilities in Sydney and the over use of technological interventions during childbirth.     

Conducting research using web-based questionnaires: Practical,methodological, and ethical considerations

The use of the internet for social science research is becoming increasingly common. This paper outlines practical, methodological and ethical issues for researchers to consider when using web-based questionnaires. This is illustrated by consideration of the authors' own experience of conducting a study into the phenomenon of self-harm.     

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.     

Testing parallelism of regression lines against ordered alternatives

For the problem of testing the equality of slopes of several regression lines against the alternative that the slopes are in increasing (decreasing) order of magnitude, two types of tests are proposed. These are the likelihood ratio test and a test that depends on suitable linear combination of one group statistics. Rank analogues of the two tests are also examined.     

Cross-Validated Assessments of Test Scoring Models

On a multiple choice test in which each item has r alternative options, a given number c of which are correct, various scoring models have been proposed. In one case the test-taker is allowed to choose any size solution subset and he/she is graded according to whether the subset is small and according to how many correct answers the subset contains. In a second case the test-taker is allowed to select only solution subsets of a prespecified maximum size and is graded as above. The first case is analogous to the situation where the test-taker is given a set of r options with each question; each question calls for a solution which consists of selecting that subset of the r responses which he/she believes to be correct. In the second case, when the prespecified solution subset is restricted to be of size at most one, the resulting scoring model corresponds to the usual model, referred to below as standard. The number c of correct options per item is usually known to the test-taker in this case.

Scoring models are evaluated according to how well they correctly identify the total scores of the individuals in the class of test-takers. Loss functions are constructed which penalize scoring models resulting in student scores which are not associated with the students true (or average) total score on the exam. Scoring models are compared on the basis of cross-validated assessments of the loss incurred by using each of the given models. It is shown that in many cases the assessment of the loss for scoring models which allow students the opportunity to choose more than one option for each question are smaller than the assessment of the loss for the standard scoring model.     

The effects on the distributions of sample canonical correlations under nonnormality

In this paper, we study the effects of nonnormality on the distributions of sample canonical correlations when the population canonical correlations are simple. In order to achieve the purpose, we derive asymptotic expansion formulas for the distributions of a function of the canonical correlations as well as the individual canonical correlations under nonnormal populations. We particularly discuss the distribution of sample canonical correlations under the class of elliptical population. These expansions are given by using a perturbation method. Simulation results are also given.     

Asymptotic properties of the complex valued non-linear regression model

The non-linear regression model, when the parameters are complex valued is considered here. Jennrich(1969) considered the non-linear regression model when the parameters are real valued. He first rigorously proved the existence of the least square estimator and showed its consistency properties and asymptotic normality. In this paper we generalise the idea for the com-plex parameters case. Large sample properties of the proposed estimator has been studied.     

Non-linear models 1

This is the first application of a new method for testing stationary random point processes. Consider the class of all stationary ergodic point processes on the real line with arbitrary dependences among the inter–point distances (spacing).The hypothesis is :The observed process φ is a homogeneous Poisson process or more (resp.less) regular than a Poisson process.The sample is the vector of the first n points t₁, …,t_n.There is a close relation between our method for testing and queueing theory: For finding an appropriate test statistic, we observe the behaviour of a single server queue with the input φ.A table of critical values is given.     

A cubic smoothing spline based lack of fit test for nonlinear regression models

The use of a statistic based on cubic spline smoothing is considered for testing nonlinear regression models for lack of fit. The statistic is defined to be the Euclidean squared norm of the smoothed residual vector obtained from fitting the nonlinear model, The asymptotic distribution of the statistic is derived under suitable smooth local alternatives and a numerical example is presented.