898 resultados para small sample biases
Resumo:
In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression
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Small sample properties are of fundamental interest when only limited data is avail-able. Exact inference is limited by constraints imposed by speci.c nonrandomizedtests and of course also by lack of more data. These e¤ects can be separated as we propose to evaluate a test by comparing its type II error to the minimal type II error among all tests for the given sample. Game theory is used to establish this minimal type II error, the associated randomized test is characterized as part of a Nash equilibrium of a .ctitious game against nature.We use this method to investigate sequential tests for the di¤erence between twomeans when outcomes are constrained to belong to a given bounded set. Tests ofinequality and of noninferiority are included. We .nd that inference in terms oftype II error based on a balanced sample cannot be improved by sequential sampling or even by observing counter factual evidence providing there is a reasonable gap between the hypotheses.
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A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.
Resumo:
In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression
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The lithic record from the Solent River and its tributaries is re-examined in the light of recent interpretations about the changing demography of Britain during the Lower and early Middle Palaeolithic. Existing models of the terrace stratigraphies in the Solent and its tributary areas are reviewed and the corresponding archaeological record (specifically handaxes) for each terrace is assessed to provide models for the relative changes in human occupation through time. The Bournemouth area is studied in detail to examine the effects of quarrying and urbanisation on collection history and on the biases it introduces to the record. In addition, the effects of reworking of artefacts from higher into lower terraces are assessed, and shown to be a significant problem. Although there is very little absolute dating available for the Solent area, a cautious interpretation of the results from these analyses would suggest a pre-Marine Isotope Stage (MIS) 12 date for the first appearance of humans, a peak in population between MIS 12 and 10, and a decline in population during MIS 9 and 8. Owing to poor contextual data and small sample sizes, it is not clear when Levallois technology was introduced. This record is compared and contrasted to that from the Thames Valley. It is suggested that changes in the palaeogeography of Britain, in particular land connections to the continent, might have contributed to differences in the archaeological records from the Solent and Thames regions.
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This paper proposes and tests a new framework for weighting recursive out-of-sample prediction errors according to their corresponding levels of in-sample estimation uncertainty. In essence, we show how to use the maximum possible amount of information from the sample in the evaluation of the prediction accuracy, by commencing the forecasts at the earliest opportunity and weighting the prediction errors. Via a Monte Carlo study, we demonstrate that the proposed framework selects the correct model from a set of candidate models considerably more often than the existing standard approach when only a small sample is available. We also show that the proposed weighting approaches result in tests of equal predictive accuracy that have much better sizes than the standard approach. An application to an exchange rate dataset highlights relevant differences in the results of tests of predictive accuracy based on the standard approach versus the framework proposed in this paper.
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The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.
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Some patients with obsessive-compulsive disorder (OCD) exhibit an unsatisfactory reduction in symptom severity despite being treated with all the available therapeutic alternatives. The clinical variables associated with treatment-refractoriness in OCD are inconsistently described in the literature.Methods: To investigate factors associated with treatment-reftactoriness of patients with OCD, we conducted a case-control study, comparing 23 patients with treatment-refractory OCD to 26 patients with treatment-responding OCD.Results: the factors associated with refractoriness of OCD were higher severity of symptoms since the onset of OCD (P < 0.001), chronic course (p=0.003), lack of a partner (p=0.037), unemployment (p=0.025), low economic status (p=0.015), presence of obsessive-compulsive symptoms of sexual/religious content (p=0.043), and higher scores on family accommodation (P < 0.001). Only the three latter variables remained significantly associated with treatment-reftactoriness after regression analyses. Limitations: small sample size, the biases and drawbacks inherent to a case-control study, and the inclusion criteria used to define the study groups may have limited the generalisation of the results.Conclusion: A major strength of this study is the systematic and structured evaluation of a vast array of variables related to the clinical expression of OCD, including epigenetic factors and ratings derived from instruments evaluating family accommodation. The presence of sexual/religious symptoms, low economic status and high modification on family function due to OCD were independently associated with, treatment-refractoriness. Future longitudinal studies are warranted to verify if these variables represent predictive factors of treatment non-response. (c) 2006 Elsevier B.V. All rights reserved.
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This article examines new product development (NPD) in small and medium-sized Brazilian enterprises (SMEs) in two technology-based industries: medical devices and process control automation devices. A conceptual model that categorizes factors that contribute to the success of a new product was established. The data were collected from a sample of 62 Brazilian SMEs. The conceptual model was tested to examine the relationships between NPD practices and new product success. Data analysis reveals that new product success in medical device companies is related to organizational characteristics such as NPD proficiency and marketing skills; while in process control automation device companies, they deal in a large degree with product differentiation, innovation and capability to analyze the targeted market. Due to the relatively small sample size, caution should be exercised when interpreting the results.
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Organic farming means a holistic application of agricultural land-use, hence, this study aimed to assess ecological and socio-economic aspects that show benefits of the strategy and achievements of organic farming in comparison to conventional farming in Darjeeling District, State of West Bengal, India and Kanagawa Prefecture/Kanto in Central Japan. The objective of this study has been empirically analysed on aspects of crop diversity, yield, income and sales prices in the two study regions, where 50 households each, i.e. in total 100 households were interviewed at farm-level. Therefore, the small sample size does not necessarily reflect the broad-scale of the use and benefit of organic farming in both regions. The problems faced in mountainous regions in terms of agriculture and livelihoods for small-scale farmers, which are most affected and dependant on their immediate environment, such as low yields, income and illegal felling leading to soil erosion and landslides, are analyzed. Furthermore, factors such as climate, soils, vegetation and relief equally play an important role for these farmers, in terms of land-use. To supplement and improve the income of farmers, local NGOs have introduced organic farming and high value organic cash crops such as ginger, tea, orange and cardamom and small income generating means (floriculture, apiary etc.). For non-certified and certified organic products the volume is given for India, while for Japan only certified organic production figures are given, as there are several definitions for organic in Japan. Hence, prior to the implementation of organic laws and standards, even reduced chemical input was sold as non-certified organic. Furthermore, the distribution and certification system of both countries are explained in detail, including interviews with distribution companies and cooperatives. Supportive observations from Kanagawa Prefecture and the Kanto region are helpful and practical suggestions for organic farmers in Darjeeling District. Most of these are simple and applicable soil management measures, natural insect repelling applications and describe the direct marketing system practiced in Japan. The former two include compost, intercropping, Effective Microorganisms (EM), clover, rice husk charcoal and wood vinegar. More supportive observations have been made at organic and biodynamic tea estates in Darjeeling District, which use citronella, neem, marigold, leguminous and soil binding plants for soil management and natural insect control. Due to the close ties between farmers and consumers in Japan, certification is often neither necessary nor wanted by the producers. They have built a confidence relationship with their customers; thus, such measures are simply not required. Another option is group certification, instead of the expensive individual certification. The former aims at lower costs for farmers who have formed a cooperative or a farmers' group. Consumer awareness for organic goods is another crucial aspect to help improve the situation of organic farmers. Awareness is slightly more advanced in Kanto than in Darjeeling District, as it is improved due to the close (sales) ties between farmers and consumers in Kanto. Interviews conducted with several such cooperatives and companies underline the positive system of TEIKEI. The introduction of organic farming in the study regions has shown positive effects for those involved, even though it still in its beginning stages in Darjeeling District. This study was only partly able to assess the benefits of organic agriculture at its present level for Darjeeling District, while more positively for the organic farmers of Kanto. The organic farming practice needs further improvement, encouragement and monitoring for the Darjeeling District farmers by locals, consumers, NGOs and politicians. The supportive observations from Kanagawa Prefecture and the Kanto region are a small step in this direction, showing how, simple soil improvements and thus, yield and income increases, as well as direct sales options can enhance the livelihood of organic farmers without destroying their environment and natural resources.
Resumo:
Power calculations in a small sample comparative study, with a continuous outcome measure, are typically undertaken using the asymptotic distribution of the test statistic. When the sample size is small, this asymptotic result can be a poor approximation. An alternative approach, using a rank based test statistic, is an exact power calculation. When the number of groups is greater than two, the number of calculations required to perform an exact power calculation is prohibitive. To reduce the computational burden, a Monte Carlo resampling procedure is used to approximate the exact power function of a k-sample rank test statistic under the family of Lehmann alternative hypotheses. The motivating example for this approach is the design of animal studies, where the number of animals per group is typically small.
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Objective: The Ile462Val substitution in the cytochrome P450 1A1 gene (CYP1A1) results in increased enzymatic activity. Preliminary data suggesting a link between this polymorphism and lung cancer risk in Caucasians are inconsistent, reflecting small sample sizes and the relatively low frequency of the variant. Methods: The data set consisted of 1050 primary non-small cell lung cancer cases and 581 controls, a large homogenous population designed specifically to address previous inconsistencies. Patients were genotyped using a PCR-RFLP technique. Results: Carriers of the valine allele, CYP1A1*2C, (Ile/Val or Val/Val genotypes) were significantly over-represented in non-small cell lung cancer compared to controls (OR=1.9; 95% CI=1.2-2.9; p=0.005) when adjusted for confounders, particularly in women (OR=4.6; 95% CI=1.7-12.4; p=0.003). The valine variant was statistically significantly over-represented in cases of lung cancer younger than the median age (64 years) (OR=2.5; 95% CI=1.3-4.8; p=0.005) and cases with less than the median cumulative tobacco-smoke exposure (46 pack-years) (OR=2.4; 95% CI=1.3-4.7; p=0.007). Conclusions: These new data establish an association between the CYP1A1 Ile462Val polymorphism and the risk of developing non-small cell lung cancer, especially among women.
Resumo:
Objective: To devise more-effective physical activity interventions, the mediating mechanisms yielding behavioral change need to be identified. The Baron-Kenny method is most commonly used. but has low statistical power and May not identify mechanisms of behavioral change in small-to-medium size Studies. More powerful statistical tests are available, Study Design and Setting: Inactive adults (N = 52) were randomized to either a print or a print-plus-telephone intervention. Walking and exercise-related social support Were assessed at baseline, after file intervention, and 4 weeks later. The Baron-Kenny and three alternative methods of mediational analysis (Freedman-Schatzkin; MacKinnon et al.: bootstrap method) were used to examine the effects of social support on initial behavior change and maintenance. Results: A significant mediational effect of social support on initial behavior change was indicated by the MacKinnon et al., bootstrap. and. marginally. Freedman-Schatzkin methods, but not by the Baron-Kenny method. No significant mediational effecl of social support on maintenance of walking was found. Conclusions: Methodologically rigorous intervention studies to identify mediators of change in physical activity are costly and labor intensive, and may not be feasible with large samples. The Use of statistically powerful tests of mediational effects in small-scale studies can inform the development of more effective interventions. (C) 2006 Elsevier Inc. All rights reserved.
Resumo:
This study is concerned with examining the application of marketing during the start-up, development and growth of small firms in the West Midlands. As an exploratory study, it provides evidence to support the central hypothesis of the thesis that whilst many small firms have the potential to progress through to the successful growth stage of development, they fail to do so because of their owner-managers' orientation towards production and selling and because they do not apply formal marketing during the initial stages of business development. A comparative approach to studying marketing in indigenous and Asian firms is adopted in an attempt to fill a gap in the literature on the characteristics and differences in the formation and development processes of these two groups of enterprises. The study has three main objectives and is based on qualitative research techniques of in-depth interviews, case studies and longitudinal studies among sixty-six firms representing the key activities of the small firms sector of the local economy. Firstly, it investigates owner-managers' orientation in developing and managing new and established businesses and explores the sources of, and changes in their orientation during the various stages of development. Secondly, it assesses the owner-manager's awareness and understanding of what constitutes the marketing function and investigates what aspects of marketing are applied during the different stages of business development. Finally, the study monitors and evaluates the outcomes and implications of applying formal marketing techniques in a small sample of firms over a period of two years. The thesis concludes by using the findings of the study to contribute additions to existing models of growth and by proposing new models of evolution and application of marketing in small firms.
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Background: Preclinical evidence suggests that statins could delay cancer progression. Previous epidemiological findings have been inconsistent and some have been limited by small sample sizes, as well as certain time-related biases. This study aimed to investigate whether breast cancer patients who were exposed to statins had reduced breast cancer-specific mortality. Methods: We conducted a retrospective cohort study of 15,140 newly diagnosed invasive breast cancer patients diagnosed from 2009 to 2012 within the Scottish Cancer Registry. Dispensed medication usage was obtained from linkages to the Scottish Prescribing Information System and breast cancer-specific deaths were identified from National Records of Scotland Death Records. Using time-dependent Cox regression models, hazard ratios (HR) and 95 % confidence intervals (CI) were calculated for the association between post-diagnostic exposure to statins (including simvastatin) and breast cancer-specific mortality. Adjustments were made for a range of potential confounders including age at diagnosis, year of diagnosis, cancer stage, grade, cancer treatments received, comorbidities, socioeconomic status and use of aspirin. Results: A total of 1,190 breast cancer-specific deaths occurred up to January 2015. Overall, after adjustment for potential confounders, there was no evidence of an association between statin use and breast cancer-specific death (adjusted HR 0.93, 95 % CI 0.77, 1.12). No significant associations were observed in dose–response analyses or in analysis of all-cause mortality. For simvastatin use specifically, a weak non-significant reduction in breast cancer-specific mortality was observed compared to non-users (adjusted HR 0.89, 95 % CI 0.73, 1.08). Statin use before diagnosis was weakly associated with a reduction in breast cancer-specific mortality (adjusted HR 0.85, 95 % CI 0.74, 0.98). Conclusion: Overall, we found little evidence of a protective association between post-diagnostic statin use and cancer-specific mortality in a large nation-wide cohort of breast cancer patients. These findings will help inform the decision whether to conduct randomised controlled trials of statins as an adjuvant treatment in breast cancer.