852 resultados para LONGITUDINAL DATA
Resumo:
Loading of the femoral neck (FN) is dominated by bending and compressive stresses. We hypothesize that adaptation of the FN to physical activity would be manifested in the cross-sectional area (CSA) and section modulus (Z) of bone, indices of axial and bending strength, respectively. We investigated the influence of physical activity on bone strength during adolescence using 7 years of longitudinal data from 109 boys and 121 girls from the Saskatchewan Paediatric Bone and Mineral Accrual Study (PBMAS). Physical activity data (PAC-Q physical activity inventory) and anthropometric measurements were taken every 6 months and DXA bone scans were measured annually (Hologic QDR2000, array mode). We applied hip structural analysis to derive strength and geometric indices of the femoral neck using DXA scans. To control for maturation, we determined a biological maturity age defined as years from age at peak height velocity (APHV). To account for the repeated measures within individual nature of longitudinal data, multilevel random effects regression analyses were used to analyze the data. When biological maturity age and body size (height and weight) were controlled, in both boys and girls, physical activity was a significant positive independent predictor of CSA and Z of the narrow region of the femoral neck (P < 0.05). There was no independent effect of physical activity on the subperiosteal width of the femoral neck. When leg length and leg lean mass were introduced into the random effects models to control for size and muscle mass of the leg (instead of height and weight), all significant effects of physical activity disappeared. Even among adolescents engaged in normal levels of physical activity, the statistically significant relationship between physical activity and indices of bone strength demonstrate that modifiable lifestyle factors like exercise play an important role in optimizing bone strength during the growing years. Physical activity differences were explained by the interdependence between activity and lean mass considerations. Physical activity is important for optimal development of bone strength. (c) 2005 Elsevier Inc. All rights reserved.
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In some contexts data envelopment analysis (DEA) gives poor discrimination on the performance of units. While this may reflect genuine uniformity of performance between units, it may also reflect lack of sufficient observations or other factors limiting discrimination on performance between units. In this paper, we present an overview of the main approaches that can be used to improve the discrimination of DEA. This includes simple methods such as the aggregation of inputs or outputs, the use of longitudinal data, more advanced methods such as the use of weight restrictions, production trade-offs and unobserved units, and a relatively new method based on the use of selective proportionality between the inputs and outputs. © 2007 Springer Science+Business Media, LLC.
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The results of the present longitudinal study demonstrate the importance of implicit leadership theories (ILTs) for the quality of leader-member exchanges (LMX) and employees' organizational commitment, job satisfaction, and well-being. Results based on a sample of 439 employees who completed the study questionnaires at 2 time points showed that the closer employees perceived their actual manager's profile to be to the ILTs they endorsed, the better the quality of LMX. Results also indicated that the implicit-explicit leadership traits difference had indirect effects on employee attitudes and well-being. These findings were consistent across employee groups that differed in terms of job demand and the duration of manager-employee relation, but not in terms of motivation. Furthermore, crossed-lagged modeling analyses of the longitudinal data explored the possibility of reciprocal effects between implicit-explicit leadership traits difference and LMX and provided support for the initially hypothesized direction of causal effects.
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2010 Mathematics Subject Classification: 62J99.
The Long-Term impact of Business Support? - Exploring the Role of Evaluation Timing using Micro Data
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The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.
The long-term impact of business support? - Exploring the role of evaluation timing using micro data
Resumo:
The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.
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Purpose: Depression in older females is a significant and growing problem. Females who experience life stressors across the life span are at higher risk for developing problems with depression than their male counterparts. The primary aim of this study was (a) to examine gender-specific differences in the correlates of depression in older primary care patients based on baseline and longitudinal analyses; and (b) to examine the longitudinal effect of biopsychosocial risk factors on depression treatment outcomes in different models of behavioral healthcare (i.e., integrated care and enhanced referral). Method: This study used a quantitative secondary data analysis with longitudinal data from the Primary Care Research in Substance Abuse and Mental Health for Elderly (PRISM-E) study. A linear mixed model approach to hierarchical linear modeling was used for analysis using baseline assessment, and follow-up from three-month and six-month. Results: For participants diagnosed with major depressive disorder female gender was associated with increased depression severity at six-month compared to males at six-month. Further, the interaction between gender and life stressors found that females who reported loss of family and friends, family issues, money issues, medical illness was related to higher depression severity compared to males whereas lack of activities was related to lower depression severity among females compared to males. Conclusion: These findings suggest that gender moderated the relationship between specific life stressors and depression severity similar to how a protective factor can impact a person's response to a problem and reduce the negative impact of a risk factor on a problem outcome. Therefore, life stressors may be a reliable predictor of depression for both females and males in either behavioral health treatment model. This study concluded that life stressors influence males basic comfort, stability, and survival whereas life stressors influence females' development, personal growth, and happiness; therefore, life stressors may be a useful component to include in gender-based screening and assessment tools for depression. ^
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In longitudinal data analysis, our primary interest is in the regression parameters for the marginal expectations of the longitudinal responses; the longitudinal correlation parameters are of secondary interest. The joint likelihood function for longitudinal data is challenging, particularly for correlated discrete outcome data. Marginal modeling approaches such as generalized estimating equations (GEEs) have received much attention in the context of longitudinal regression. These methods are based on the estimates of the first two moments of the data and the working correlation structure. The confidence regions and hypothesis tests are based on the asymptotic normality. The methods are sensitive to misspecification of the variance function and the working correlation structure. Because of such misspecifications, the estimates can be inefficient and inconsistent, and inference may give incorrect results. To overcome this problem, we propose an empirical likelihood (EL) procedure based on a set of estimating equations for the parameter of interest and discuss its characteristics and asymptotic properties. We also provide an algorithm based on EL principles for the estimation of the regression parameters and the construction of a confidence region for the parameter of interest. We extend our approach to variable selection for highdimensional longitudinal data with many covariates. In this situation it is necessary to identify a submodel that adequately represents the data. Including redundant variables may impact the model’s accuracy and efficiency for inference. We propose a penalized empirical likelihood (PEL) variable selection based on GEEs; the variable selection and the estimation of the coefficients are carried out simultaneously. We discuss its characteristics and asymptotic properties, and present an algorithm for optimizing PEL. Simulation studies show that when the model assumptions are correct, our method performs as well as existing methods, and when the model is misspecified, it has clear advantages. We have applied the method to two case examples.
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Case study research has the advantage of investigating issues that are embedded within the context of the case. A novel approach to investigation of the implementation of service innovation process has been adopted through a longitudinal ethnographic case study. This approach was found useful, as the outcome of the study was intended to be an in-depth understanding of firm’s current innovation practices and its consequences with the implementation of a novel business process. In this applied research, an array of longitudinal data was generated chiefly through the technique of participant-observation. Participant-observation as a qualitative or naturalistic method has its roots in ethnographic research. Participant-observation involves “participating in the social world, in whatever role, and reflecting on the products of that participation” (Hammersley & Atkinson, 1983, p.16). This method offers a degree of understanding of the context under study that can come only from personal experience. In this presentation, I discuss the role of the researcher-practitioner as participant-observer and the usefulness of ethnographic case study methodology and participant-observation technique to investigating service innovation practices that are embedded within the context-specific setting of the case.
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Thesis (Ph.D.)--University of Washington, 2016-08
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To analyse the sensitivity and specificity of clinical indicators of ineffective airway clearance in children with congenital heart disease and to identify the indicators that have high predictive power. The precise establishment of nursing diagnoses has been found to be one of the factors contributing to higher quality of care and cost reduction in healthcare institutions. The use of indicators to diagnose ineffective airway clearance could improve care of children with congenital heart disease. Longitudinal study. Participants consisted of 45 children, <= 1 year of age, with congenital heart disease, who had not had definitive or palliative surgical correction. Six assessments were made at 2-day intervals. Each clinical indicator was defined based on previously established operational criteria. Sensitivity, specificity and positive and negative predictive values of each indicator were calculated based on a model for the longitudinal data. A nursing diagnosis of ineffective airway clearance was made in 31% of patients on the first assessment, rising to 71% on the last assessment, for a 40% increase. Sensitivity was highest for Changes in Respiratory Rates/Rhythms (0.99), followed by Adventitious Breath Sounds (0.97), Sputum Production (0.85) and Restlessness (0.53). Specificity was higher for Sputum Production (0.92), followed by Restlessness (0.73), Adventitious Breath Sounds (0.70) and Changes in Respiratory Rates/Rhythms (0.17). The best positive predictive values occurred for Sputum Production (0.93) and Adventitious Breath Sounds (0.80). Adventitious Breath Sounds followed by Sputum Production were the indicators that had the best overall sensitivity and specificity as well as the highest positive predictive values. The use of simple indicators in nursing diagnoses can improve identification of ineffective airway clearance in children with congenital heart disease, thus leading to early treatment of the problem and better care for these children.
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The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.
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More than 41,000 women aged 18-23, 45-50, and 70-75 years in 1996 are participating in the Australian Longitudinal Study on Women's Health (Women's Health Australia). Baseline surveys were conducted for all three cohorts in 1996, and the first follow-up survey of the mid-age group in 1998 has achieved a response rate exceeding 90%. The main findings so far reflect the large differences in the life experiences of the three cohorts. The young women report high levels of stress. The physical and mental health of those with young children is worse than for those without children, but confounding by sociodemographic characteristics may account for the differences. Two thirds of young women in the healthy weight or underweight range would like to weigh less, and early onset of dieting is associated with poorer physical and mental health. Most of the women in the mid-age group have multiple roles-in paid work, home duties, and caring for children and other dependents. The potential of the study to investigate the long-term impact of such busy lives on health outcomes is considerable. At this stage, the main health issues for these women relate to tiredness, weight gain, and menopause. The older cohort presents a picture of positive aging. These women are heavier users of health services than the mid-age and younger women, and they are also more satisfied with these services. Although their physical health is poorer, their mental health is better, and they report less stress than women in the other two cohorts. The follow-up survey of this group, planned for 1999, will focus on the coping strategies used by these women. An overall goal of the project is to understand the interactions among social roles, life events, and women's health in order to provide a basis for improved health policies and services. Analysis of these interactions, which relies on both quantitative and qualitative data, poses many challenges that will be addressed as the longitudinal data become available.
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To investigate whether there are gender differences in the bone geometry of the proximal femur during the adolescent years we used an interactive computer program ?Hip Strength Analysis? developed by Beck and associates (Beck et al., Invest Radiol. 1990,25:6-18.) to derive femoral neck geometry parameters from DXA bone scans (Hologic 2000, array mode). We analyzed a longitudinal data-set collected on 70 boys and 68 girls over a seven year period. Distance and velocity curves for height were fitted for each child utilizing a cubic spline procedure and the age of peak height velocity (PHV) was determined. To control for maturational differences between children of the same chronological age and between boys and girls, section modulus (Z) an index of bending strength, cross sectional area of bone (CSA), sub-periosteal width (SPW), and BMD values at the neck and shaft of the proximal femur were determined for points on each individual?s curve at the age of PHV and one and two years on either side of peak. To control for size differences, height and weight were introduced as co-variates in the two-way analyses of variance looking at gender over time measured at the maturational age points (-2, -1, age of PHV, +1, +2). The following figure presents the results of the analyses on two variables, BMD and Z at neck and shaft regions:After the age of peak linear growth (PHV), independent of body size, there was a gender difference in BMD at the shaft but not at the neck. Section modulus at both sites indicated that male bones became significantly stronger after PHV. Underlying these maturational changes, male bones became wider (SPW) after PHV in both the neck and shaft and enclosed more material (CSA) at all maturational age points at both regions. These results call into question the emphasis on using BMD as a measure of skeletal integrity in growing children
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The literature examining purported relationships between ownership of companion animals and health is extremely heterogeneous. While much of the descriptive literature tends to support benefits of animal companionship, large scale, controlled research yields inconsistent and even contradictory findings on several issues, including associations with cardiovascular disease, mood and wellbeing. In an analysis of a large longitudinal data-set from the Australian Longitudinal Study on Women's Health, a prospective study of a nationally representative sample of more than 12,000 older women, difficulties with disentangling the effects of powerful demographic variables and age-related factors from the specific effects of pet ownership became apparent. Both cross-sectional and longitudinal analyses demonstrated that associations between mental and physical health and pet ownership as well as changes in pet ownership over time were weak and inconsistent compared to the large effects of living arrangements and other demographic variables. As sociodemographic variables relate strongly to both health and opportunities for pet ownership, this high level of confounding means it is unlikely that the impact of the specific variable of pet ownership on health can be ascertained from such studies. Rather, well-designed experimental studies, wherein the majority of such confounding variables can be held constant or at least somewhat controlled, are needed.