The Experts below are selected from a list of 70650 Experts worldwide ranked by ideXlab platform
Wayne R Landsman - One of the best experts on this subject based on the ideXlab platform.
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relative valuation roles of equity book value and net income as a function of financial health
Journal of Accounting and Economics, 1998Co-Authors: Mary E Barth, William H Beaver, Wayne R LandsmanAbstract:Abstract This study tests predictions that pricing multiples on and incremental Explanatory Power of equity book value (net income) increase (decrease) as financial health decreases. Tests using a sample of 396 bankrupt firms and tests using a larger, pooled sample both yield inferences consistent with predictions. Findings are robust to inclusion of controls for industry, size, return-on-equity, and volatility of equity returns. Equity book value and net income multiples and incremental Explanatory Power vary predictably across three illustrative industries, selected based on the likely extent of unrecognized intangible assets.
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valuation characteristics of equity book value and net income tests of the abandonment option hypothesis
Social Science Research Network, 1996Co-Authors: Mary E Barth, William H Beaver, Wayne R LandsmanAbstract:This study tests hypotheses about effects of the abandonment option on equity book value and net income valuation characteristics. As predicted, pricing multiples on and Explanatory Power of book equity (net income) increase (decrease) as firms approach liquidation or bankruptcy. Also, pricing multiples on and Explanatory Power of book equity (net income) are higher (lower) for approximately one-half of Compustat firms classified as less financially healthy, providing evidence inferences are not limited to firms approaching extreme financial distress. Net income and equity book value valuation characteristics vary predictably across three illustrative industries, selected based on extent of unrecognized intangible assets.
Nicole Barger - One of the best experts on this subject based on the ideXlab platform.
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maximizing Explanatory Power in stereological data collection a protocol for reliably integrating optical fractionator and multiple immunofluorescence techniques
Frontiers in Neuroanatomy, 2018Co-Authors: Anna Kreutz, Nicole BargerAbstract:With the promise of greater reliability and replicability of estimates, stereological techniques have revolutionized data collection in the neurosciences. At the same time, improvements in immunohistochemistry and fluorescence imaging technologies have facilitated easy application of immunofluorescence protocols, allowing for isolation of multiple target proteins in one tissue sample. Combining multiple immunofluorescence labeling with stereological data collection can provide a Powerful tool to maximize Explanatory Power and efficiency, while minimizing tissue use. Multiple cell classes, subtypes of larger populations, or different cell states can be quantified in one case and even in one sampling run. Here, we present a protocol integrating stereological data collection and multiple immunofluorescence using commonly employed widefield epifluorescence filter sets, optimized for blue (DAPI), green (FITC), and far red (CY5) channels. Our stereological protocol has been designed to accommodate the challenges of fluorescence imaging to overcome limitations like fixed filter sets, photobleaching, and uneven immunolabeling. To enhance fluorescence signal for stereological sampling, our immunolabeling protocol utilizes both high temperature antigen retrieval to improve primary antibody binding and secondary antibodies conjugated to optimally stable fluorophores. To illustrate the utility of this approach, we estimated the number of Ctip2 immunoreactive subcerebral projection neurons and NeuN immunoreactive neurons in rat cerebral cortex at postnatal day 10. We used DAPI (blue) to define the neocortex, anti-NeuN (far red) to identify neurons, and co-labeling of anti-Ctip2 (green) and anti-NeuN (far red) to isolate only subcerebral projection neurons. Our protocol resulted in estimates with low sampling error (CE 0.98) that fall within the range of published values, attesting to its efficacy. We show our immunofluorescence techniques can be used to reliably identify other cell types, e.g., different glial cell classes, to highlight the broader applications of our approach. The flexibility of the technique, increasingly reduced costs of fluorescence technologies, and savings in experimental time and tissue use make this approach valuable for neuroscientists interested in incorporating stereology to ask precise neurophysiological and neuroanatomical questions.
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Maximizing Explanatory Power in Stereological Data Collection: A Protocol for Reliably Integrating Optical Fractionator and Multiple Immunofluorescence Techniques
'Frontiers Media SA', 2018Co-Authors: Anna Kreutz, Nicole BargerAbstract:With the promise of greater reliability and replicability of estimates, stereological techniques have revolutionized data collection in the neurosciences. At the same time, improvements in immunohistochemistry and fluorescence imaging technologies have facilitated easy application of immunofluorescence protocols, allowing for isolation of multiple target proteins in one tissue sample. Combining multiple immunofluorescence labeling with stereological data collection can provide a Powerful tool to maximize Explanatory Power and efficiency, while minimizing tissue use. Multiple cell classes, subtypes of larger populations, or different cell states can be quantified in one case and even in one sampling run. Here, we present a protocol integrating stereological data collection and multiple immunofluorescence using commonly employed widefield epifluorescence filter sets, optimized for blue (DAPI), green (FITC), and far red (CY5) channels. Our stereological protocol has been designed to accommodate the challenges of fluorescence imaging to overcome limitations like fixed filter sets, photobleaching, and uneven immunolabeling. To enhance fluorescence signal for stereological sampling, our immunolabeling protocol utilizes both high temperature antigen retrieval to improve primary antibody binding and secondary antibodies conjugated to optimally stable fluorophores. To illustrate the utility of this approach, we estimated the number of Ctip2 immunoreactive subcerebral projection neurons and NeuN immunoreactive neurons in rat cerebral cortex at postnatal day 10. We used DAPI (blue) to define the neocortex, anti-NeuN (far red) to identify neurons, and co-labeling of anti-Ctip2 (green) and anti-NeuN (far red) to isolate only subcerebral projection neurons. Our protocol resulted in estimates with low sampling error (CE < 0.05) and high intrarater reliability (ICC > 0.98) that fall within the range of published values, attesting to its efficacy. We show our immunofluorescence techniques can be used to reliably identify other cell types, e.g., different glial cell classes, to highlight the broader applications of our approach. The flexibility of the technique, increasingly reduced costs of fluorescence technologies, and savings in experimental time and tissue use make this approach valuable for neuroscientists interested in incorporating stereology to ask precise neurophysiological and neuroanatomical questions
G D Batty - One of the best experts on this subject based on the ideXlab platform.
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does iq explain socio economic differentials in total and cardiovascular disease mortality comparison with the Explanatory Power of traditional cardiovascular disease risk factors in the vietnam experience study
European Heart Journal, 2009Co-Authors: G D Batty, Martin J Shipley, Ruth Dundas, Sally Macintyre, Geoff Der, Laust Hvas Mortensen, Ian J DearyAbstract:The aim of this study was to examine the Explanatory Power of intelligence (IQ) compared with traditional cardio- vascular disease (CVD) risk factors in the relationship of socio-economic disadvantage with total and CVD mortality, that is the extent to which IQ may account for the variance in this well-documented association. Methods and results Cohort study of 4289 US male former military personnel with data on four widely used markers of socio-economic position (early adulthood and current income, occupational prestige, and education), IQ test scores (early adulthood and middle-age), a range of nine established CVD risk factors (systolic and diastolic blood pressure, total blood cholesterol, HDL cholesterol, body mass index, smoking, blood glucose, resting heart rate, and forced expiratory volume in 1 s), and later mortality. We used the relative index of inequality (RII) to quantify the relation between each index of socio-economic position and mortality. Fifteen years of mortality surveillance gave rise to 237 deaths (62 from CVD and 175 from 'other' causes). In age-adjusted analyses, as expected, each of the four indices of socio-economic position was inversely associated with total, CVD, and 'other' causes of mortality, such that elevated rates were evident in the most socio-economically disadvantaged men. When IQ in middle-age was introduced to the age-adjusted model, there was marked attenuation in the RII across the socio-economic predictors for total mortality (average 50% attenuation in RII), CVD (55%), and 'other' causes of death (49%). When the nine traditional risk factors were added to the age-adjusted model, the comparable reduction in RII was less marked than that seen after IQ adjustment: all-causes (40%), CVD (40%), and 'other' mortality (43%). Adding IQ to the latter model resulted in marked, additional Explanatory Power for all outcomes in comparison to the age-adjusted analyses: all-causes (63%), CVD (63%), and 'other' mortality (65%). When we utilized IQ in early adulthood rather than middle-age as an Explanatory variable, the attenuating effect on the socio-economic gradient was less pronounced although the same pattern was still present. Conclusion In the present analyses of socio-economic gradients in total and CVD mortality, IQ appeared to offer greater expla-
Chin-lu Chyu - One of the best experts on this subject based on the ideXlab platform.
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A fuzzy linear regression model with better Explanatory Power
Fuzzy Sets and Systems, 2002Co-Authors: Chiang Kao, Chin-lu ChyuAbstract:Previous studies on fuzzy linear regression analysis have a common characteristic of increasing spreads for the estimated fuzzy responses as the independent variable increases its magnitude, which is not suitable for general cases. This paper proposes a two-stage approach to construct the fuzzy linear regression model. In the first stage, the fuzzy observations are defuzzified so that the traditional least-squares method can be applied to find a crisp regression line showing the general trend of the data. In the second stage, the error term of the fuzzy regression model, which represents the fuzziness of the data in a general sense, is determined to give the regression model the best Explanatory Power for the data. The results from two examples, one with crisp data and the other with fuzzy data for the independent variable, indicate that the two-stage method proposed in this paper has better performance than the previous studies.
Mary E Barth - One of the best experts on this subject based on the ideXlab platform.
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relative valuation roles of equity book value and net income as a function of financial health
Journal of Accounting and Economics, 1998Co-Authors: Mary E Barth, William H Beaver, Wayne R LandsmanAbstract:Abstract This study tests predictions that pricing multiples on and incremental Explanatory Power of equity book value (net income) increase (decrease) as financial health decreases. Tests using a sample of 396 bankrupt firms and tests using a larger, pooled sample both yield inferences consistent with predictions. Findings are robust to inclusion of controls for industry, size, return-on-equity, and volatility of equity returns. Equity book value and net income multiples and incremental Explanatory Power vary predictably across three illustrative industries, selected based on the likely extent of unrecognized intangible assets.
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valuation characteristics of equity book value and net income tests of the abandonment option hypothesis
Social Science Research Network, 1996Co-Authors: Mary E Barth, William H Beaver, Wayne R LandsmanAbstract:This study tests hypotheses about effects of the abandonment option on equity book value and net income valuation characteristics. As predicted, pricing multiples on and Explanatory Power of book equity (net income) increase (decrease) as firms approach liquidation or bankruptcy. Also, pricing multiples on and Explanatory Power of book equity (net income) are higher (lower) for approximately one-half of Compustat firms classified as less financially healthy, providing evidence inferences are not limited to firms approaching extreme financial distress. Net income and equity book value valuation characteristics vary predictably across three illustrative industries, selected based on extent of unrecognized intangible assets.
