Estimation Of Relative Frequency Research Articles

Epidemiology and clinical features of paroxysmal hemicrania: Asystematic review and meta-analysis.

To assess the prevalence or relative frequency of paroxysmal hemicrania and its clinical features in the adult general population and among adult patients evaluated for headache in tertiary care. Paroxysmal hemicrania is a rare trigeminal autonomic cephalalgia with characteristic attacks of headache, associated cranial autonomic symptoms and signs, and an absolute response to indomethacin. Its epidemiological burden remains unknown in both the adult general population and among adult patients evaluated for headache in a tertiary care setting. Moreover, the frequencies of the clinical features associated with paroxysmal hemicrania have not been well established. A literature search of PubMed and Embase was conducted from January 1, 1988, to January 20, 2023. Eligible for inclusion were observational studies reporting the point prevalence or relative frequency of paroxysmal hemicrania or its clinical features in the adult general population or among adult patients evaluated for headache in tertiary care. Two independent investigators (M.J.H. and J.G.L.) performed the title, abstract, and full-text article screening. Each included study's risk of bias was critically appraised using the Joanna Briggs Institute Critical Appraisal Checklist for Studies Reporting Prevalence Data. Estimates of prevalence or relative frequency were calculated using a random-effects meta-analysis. The between-study heterogeneity was assessed using the I2 statistic and further explored with meta-regression. This study was pre-registered on PROSPERO (identifier: CRD42023391127). A total of 17 clinic-based studies and one population-based study met the eligibility criteria. Importantly, an overall high risk of bias was observed across the eligible studies. The relative frequency of paroxysmal hemicrania was estimated to be 0.3% (95% CI, 0.2%-0.5%) among adult patients evaluated for headache in tertiary care with considerable heterogeneity (I2 = 76.4%). No cases with paroxysmal hemicrania were identified among 1,838 participants in a population-based sample. Moreover, the most prevalent cranial autonomic symptoms were lacrimation (77.3% [95% Cl, 62.7%-87.3%]), conjunctival injection (75.0% [95% Cl, 60.3%-85.6%]), and nasal congestion (47.7% [95% Cl, 33.6%-62.3%]). Our findings suggest that paroxysmal hemicrania is a rare disorder among adults evaluated for headache in tertiary care, while its prevalence in the general population remains unknown. Further studies focusing on the clinical features of paroxysmal hemicrania are warranted.

Making decisions with evidential probability and objective Bayesian calibration inductive logics

Calibration inductive logics are based on accepting estimates of relative frequencies, which are used to generate imprecise probabilities. In turn, these imprecise probabilities are intended to guide beliefs and decisions — a process called “calibration”. Two prominent examples are Henry E. Kyburg's system of Evidential Probability and Jon Williamson's version of Objective Bayesianism. There are many unexplored questions about these logics. How well do they perform in the short-run? Under what circumstances do they do better or worse? What is their performance relative to traditional Bayesianism?In this article, we develop an agent-based model of a classic binomial decision problem, including players based on variations of Evidential Probability and Objective Bayesianism. We compare the performances of these players, including against a benchmark player who uses standard Bayesian inductive logic. We find that the calibrated players can match the performance of the Bayesian player, but only with particular acceptance thresholds and decision rules. Among other points, our discussion raises some challenges for characterising “cautious” reasoning using imprecise probabilities. Thus, we demonstrate a new way of systematically comparing imprecise probability systems, and we conclude that calibration inductive logics are surprisingly promising for making decisions.

Facilitating factors and obstacles in the coordination of theoretical probability and relative frequency estimates of probability

Facilitating factors and obstacles in the coordination of theoretical probability and relative frequency estimates of probability

Premonitory symptoms in migraine: a systematic review and meta-analysis of observational studies reporting prevalence or relative frequency

BackgroundObservational studies on the prevalence of premonitory symptoms in people with migraine, preceding the headache pain (or aura) phase, have shown conflicting results. We conducted a systematic review and meta-analysis to estimate the prevalence, and relative frequency among clinic populations, of premonitory symptoms in people with migraine, overall and of the multifarious individual symptoms, and to review the methodologies used to assess them.MethodsWe searched PubMed and Embase for studies published from database inception until 31st of May 2022. Two investigators independently screened titles, abstracts, and full texts. We retrieved observational studies that reported the prevalence/relative frequency of one or more premonitory symptoms in people with migraine. Two investigators independently extracted data and assessed risk of bias. Results were pooled using random-effects meta-analysis. Our main outcomes were the percentage of people with migraine who experienced at least one premonitory symptom and the percentages who experienced different individual premonitory symptoms. To describe our outcomes, we used the terms prevalence for data from population-based samples and relative frequency for data from clinic-based samples. We also descriptively and critically assessed the methodologies used to assess these symptoms.ResultsThe pooled estimated prevalence in population-based studies of at least one premonitory symptom was 29% (95% CI: 8–63; I2 99%) and the corresponding pooled estimated relative frequency in clinic-based studies was 66% (95% CI: 45–82; I2 99%). The data from clinic-based studies only supported meta-analysis of 11 of 96 individual symptoms, with relative frequency estimates ranging from 11 to 49%. Risk of bias was determined as high in 20 studies, moderate in seven, and low in two.ConclusionsThe substantial between-study heterogeneity demands cautious interpretation of our estimates. Studies showed wide methodological variations, and many lacked rigor. Overall, the evidence was insufficient to support reliable prevalence estimation or characterization of premonitory symptoms. More data are needed, of better quality, to confirm the existence of a distinctive premonitory phase of migraine, and its features. Methodological guidelines based on expert consensus are a prerequisite.

PERCEPTION OF ESSENCE OF CONTROLLING AND ITS USE IN MANUFACTURING ENTERPRISES IN TIME OF CRISIS: DOES CONTROLLING FULFILL ITS ESSENCE?

The use of controlling in the business sphere is relatively broad and its essence can be perceived diversely by enterprises of different sectors and sizes. The aim of the research is to identify the current state of the use of controlling in Slovak manufacturing enterprises with an assessment of the perception of its essence in terms of capital structure and business performance measured by the Return on Sales (ROS). Total of 347 enterprises were asked by means of stratified sampling in 2020. Goodness-of-fit test was used when examining the representativeness of the research sample and for individual hypotheses the two-sample test of relative frequencies, relative frequency test, 95% interval estimates of relative frequencies, contingency and Pearson’s chi-square test were applied. Testing confirmed the existence of statistically significant correlation between the capital structure of manufacturing enterprises and the level of wider perception and practical use of the essence of controlling in relation to the performance measured by ROS. In conclusion is demonstrated that the potential of controlling in enterprises is not fully used, especially in the form of comprehensive secondary coordination of management and the possible directions of using it are outlined, with a positive impact on business performance.

Caracterización morfológica y faneróptica de hembras Ovino de Pelo Criollo Colombiano “OPC” Sudán

Objetivo. Esta investigación tuvo como objetivo describir la morfología cualitativa y faneróptica de hembras Ovino de Pelo Criollo Colombiano (OPC) Sudán. Materiales y métodos. Se evaluaron seis características fanerópticas y siete morfológicas cualitativas en 115 hembras Sudán Bayo y Sudán Blanco, de los departamentos Córdoba, Cesar y La Guajira. Los datos obtenidos se analizaron a través del programa estadístico InfoStat® y se estimaron las frecuencias relativas y absolutas para cada uno de los caracteres evaluados. Resultados. Los OPC Sudán Bayo se distinguieron por ser de un color de capa bayo amarillo. Los Sudán Blanco fueron de capa overo castaño, pero predominando siempre el blanco sobre el castaño. Estos ovinos se caracterizaron por poseer mucosas negra-rosadas y en menor proporción habían individuos con mucosas rosadas. Además, presentaron orejas horizontales siempre, perfiles subconvexos en más del 80% de los casos, cuellos generalmente medianos y poco musculados, grupas usualmente inclinadas, ubres parcialmente pigmentadas y también despigmentadas. Asimismo, se caracterizaron por ostentar pezuñas veteadas mayoritariamente, aunque con un alto porcentaje de pezuñas claras en las Sudán Blanco. Conclusiones. Este trabajo ha permitido caracterizar de manera específica a las OPC Sudán desde la morfología y la faneróptica, obteniéndose así información de importancia para delimitar los parámetros de pertenencia a este grupo y para la propuesta de creación de un estándar racial.

Refining algorithmic estimation of relative fundamental frequency: Accounting for sample characteristics and fundamental frequency estimation method.

Relative fundamental frequency (RFF) is a promising acoustic measure for evaluating voice disorders. Yet, the accuracy of the current RFF algorithm varies across a broad range of vocal signals. The authors investigated how fundamental frequency (fo) estimation and sample characteristics impact the relationship between manual and semi-automated RFF estimates. Acoustic recordings were collected from 227 individuals with and 256 individuals without voice disorders. Common fo estimation techniques were compared to the autocorrelation method currently implemented in the RFF algorithm. Pitch strength-based categories were constructed using a training set (1158 samples), and algorithm thresholds were tuned to each category. RFF was then computed on an independent test set (291 samples) using category-specific thresholds and compared against manual RFF via mean bias error (MBE) and root-mean-square error (RMSE). Auditory-SWIPE' for fo estimation led to the greatest correspondence with manual RFF and was implemented in concert with category-specific thresholds. Refining fo estimation and accounting for sample characteristics led to increased correspondence with manual RFF [MBE = 0.01 semitones (ST), RMSE = 0.28 ST] compared to the unmodified algorithm (MBE = 0.90 ST, RMSE = 0.34 ST), reducing the MBE and RMSE of semi-automated RFF estimates by 88.4% and 17.3%, respectively.

More than Fish – The Potential of Baited Remote Underwater Video to Assess Freshwater Herpetofauna and Dolphins

We discuss new applications of baited remote underwater video (BRUV) systems based on recordings of Amazonian freshwater fauna during a long-term fish monitoring program in the Xingu River, Brazil. BRUVs facilitated estimates of relative abundance and frequency of occurrence for species of river turtles (Podocnemis unifilis, P. expansa, Rhinoclemmys punctularia), river dolphin (Inia geoffrensis) and spectacled caiman (Caiman crocodilus) in a variety of habitats including rocky rapids, submerged sandy beaches, an artificial reservoir and the Xingu Ria.

Panel sequencing distinguishes monogenic forms of nephritis from nephrosis in children.

Alport syndrome (AS) and atypical hemolytic-uremic syndrome (aHUS) are rare forms of chronic kidney disease (CKD) that can lead to a severe decline of renal function. Steroid-resistant nephrotic syndrome (SRNS) is more common than AS and aHUS and causes 10% of childhood-onset CKD. In recent years, multiple monogenic causes of AS, aHUS and SRNS have been identified, but their relative prevalence has yet to be studied together in a typical pediatric cohort of children with proteinuria and hematuria. We hypothesized that identification of causative mutations by whole exome sequencing (WES) in known monogenic nephritis and nephrosis genes would allow distinguishing nephritis from nephrosis in a typical pediatric group of patients with both proteinuria and hematuria at any level. We therefore conducted an exon sequencing (WES) analysis for 11 AS, aHUS and thrombotic thrombocytopenic purpura-causing genes in an international cohort of 371 patients from 362 families presenting with both proteinuria and hematuria before age 25 years. In parallel, we conducted either WES or high-throughput exon sequencing for 23 SRNS-causing genes in all patients. We detected pathogenic mutations in 18 of the 34 genes analyzed, leading to a molecular diagnosis in 14.1% of families (51 of 362). Disease-causing mutations were detected in 3 AS-causing genes (4.7%), 3 aHUS-causing genes (1.4%) and 12 NS-causing genes (8.0%). We observed a much higher mutation detection rate for monogenic forms of CKD in consanguineous families (35.7% versus 10.1%). We present the first estimate of relative frequency of inherited AS, aHUS and NS in a typical pediatric cohort with proteinuria and hematuria. Important therapeutic and preventative measures may result from mutational analysis in individuals with proteinuria and hematuria.

Detection experiments with humans implicate visual predation as a driver of colour polymorphism dynamics in pygmy grasshoppers

BackgroundAnimal colour patterns offer good model systems for studies of biodiversity and evolution of local adaptations. An increasingly popular approach to study the role of selection for camouflage for evolutionary trajectories of animal colour patterns is to present images of prey on paper or computer screens to human ‘predators’. Yet, few attempts have been made to confirm that rates of detection by humans can predict patterns of selection and evolutionary modifications of prey colour patterns in nature. In this study, we first analyzed encounters between human ‘predators’ and images of natural black, grey and striped colour morphs of the polymorphic Tetrix subulata pygmy grasshoppers presented on background images of unburnt, intermediate or completely burnt natural habitats. Next, we compared detection rates with estimates of capture probabilities and survival of free-ranging grasshoppers, and with estimates of relative morph frequencies in natural populations.ResultsThe proportion of grasshoppers that were detected and time to detection depended on both the colour pattern of the prey and on the type of visual background. Grasshoppers were detected more often and faster on unburnt backgrounds than on 50% and 100% burnt backgrounds. Striped prey were detected less often than grey or black prey on unburnt backgrounds; grey prey were detected more often than black or striped prey on 50% burnt backgrounds; and black prey were detected less often than grey prey on 100% burnt backgrounds. Rates of detection mirrored previously reported rates of capture by humans of free-ranging grasshoppers, as well as morph specific survival in the wild. Rates of detection were also correlated with frequencies of striped, black and grey morphs in samples of T. subulata from natural populations that occupied the three habitat types used for the detection experiment.ConclusionsOur findings demonstrate that crypsis is background-dependent, and implicate visual predation as an important driver of evolutionary modifications of colour polymorphism in pygmy grasshoppers. Our study provides the clearest evidence to date that using humans as ‘predators’ in detection experiments may provide reliable information on the protective values of prey colour patterns and of natural selection and microevolution of camouflage in the wild.

Born in an infinite universe: A cosmological interpretation of quantum mechanics

We study the quantum measurement problem in the context of an infinite, statistically uniform space, as could be generated by eternal inflation. It has recently been argued that when identical copies of a quantum measurement system exist, the standard projection operators and Born rule method for calculating probabilities must be supplemented by estimates of relative frequencies of observers. We argue that an infinite space actually renders the Born rule redundant, by physically realizing all outcomes of a quantum measurement in different regions, with relative frequencies given by the square of the wave function amplitudes. Our formal argument hinges on properties of what we term the quantum confusion operator, which projects onto the Hilbert subspace where the Born rule fails, and we comment on its relation to the oft-discussed quantum frequency operator. This analysis unifies the classical and quantum levels of parallel universes that have been discussed in the literature, and has implications for several issues in quantum measurement theory. It also shows how, even for a single measurement, probabilities may be interpreted as relative frequencies in unitary (Everettian) quantum mechanics. We also argue that after discarding a zero-norm part of the wavefunction, the remainder consists of a superposition of indistinguishable terms, so that arguably "collapse" of the wavefunction is irrelevant, and the "many worlds" of Everett's interpretation are unified into one. Finally, the analysis suggests a "cosmological interpretation" of quantum theory in which the wave function describes the actual spatial collection of identical quantum systems, and quantum uncertainty is attributable to the observer's inability to self-locate in this collection.

Self-Referral in Medical Imaging: A Meta-Analysis of the Literature

In the current political and economic climate, there is a desire to reduce health care costs; diagnostic imaging expenditure is one area of particular interest. The authors present a meta-analysis of the relative frequency of imaging utilization in the setting of self-referral compared with that of non-self-referral and a simulation of increased cost to Medicare Part B on the basis of this relative frequency. The MEDLINE database was searched systematically. Specific inclusion criteria for relative frequency calculations were a numerator (number of patients imaged) and denominator (number of total patients seen) in each group (self-referrers and radiologist referrers). The relative risk of self-referral was determined for each group and is defined by the "relative frequency" of imaging utilization for the self-referrers divided by the frequency for the radiologist referrers. Relative frequency represents the increased (if >1) or decreased (if <1) chance of imaging by self-referrers over radiologist referrers. The meta-analysis was used to combine imaging frequencies for each referral condition of the individual studies that met inclusion criteria for an overall estimate of relative frequency, using a random-effects model to account for the variations among the studies. Relative frequency data were then used to perform a cost simulation to Medicare Part B using 2006 data. The initial search yielded 334 articles, 5 of which met the threshold for inclusion. In these 5 studies, 76,905,162 total episodes of care were analyzed. The individual relative frequency of imaging in the setting of self-referral ranged from 1.60 to 4.50. The combined relative frequency was 2.16 (95% confidence interval, 2.15-2.16) using the fixed-effects model and 2.48 (95% confidence interval, 1.90-3.24) using the random-effects model. For 2006 Government Accountability Office (GAO) data, the estimated cost of increased imaging in the setting of self-referral was $3.6 billion, but a range of costs was also provided to account for potential inaccuracies in the GAO data. The existing literature yields a combined relative frequency of imaging of 2.48 (95% confidence interval, 1.90-3.24) for self-referrers compared with non-self-referrers. Precise extrapolation of Medicare Part B costs attributable to self-referral would require changes in reporting requirements for imaging equipment ownership. Cost simulation results total billions of dollars annually and may be irrespective of potential inaccuracies in the GAO data as a result of Current Procedural Terminology(®) coding ambiguity and nontransparent reporting of equipment ownership.

Least Squares-Based Estimation of Relative Clock Offset and Frequency in Sensor Networks with High Latency

Accurate clock synchronization is essential in the operation of Sensor Networks. Algorithms for clock synchronization generally rely on estimators of the relative offset and frequency of two different clocks. Sensor Networks have limited power resources so it is important that these estimators not be too computationally intensive. For this reason a number of least squares-based estimators have been proposed, however they are not appropriate for sensor networks with significant propagation latency. For these applications, the Time Synchronization for High Latency (TSHL) protocol was developed. We seek to improve the accuracy of TSHL and thus propose, study, and demonstrate the effectiveness of several alternative least squares-based estimators.

Hierarchical Phrase-Based Grammar Extraction in Joshua:

While example-based machine translation has long used corpus information at run-time, statistical phrase-based approaches typically include a preprocessing stage where an aligned parallel corpus is split into phrases, and parameter values are calculated for each phrase using simple relative frequency estimates. This paper describes an open source implementation of the crucial algorithms presented in (Lopez, 2008) which allow direct run-time calculation of SCFG translation rules in Joshua.

Breast Cancer Risk Estimation Using the OncoVue® Model Compared to Combined GWAS Single Nucleotide Polymorphisms.

Abstract Background: We have developed a new breast cancer risk assessment model (OncoVue) that integrates information from 22 single nucleotide polymorphisms (SNPs) and 5 personal risk factors. It has been shown to effectively stratify risk in three independent validation populations. Genome wide association studies (GWAS) have identified seven candidate SNPs independently associated with breast cancer risk. Using estimates of relative risks and allele frequencies derived from these studies, a theoretical examination of these SNPs has concluded that they have the potential to modestly improve clinical risk estimation. We have examined both the OncoVue model and these GWAS SNPs in the same case-control population to determine their utility in risk estimation.Materials and Methods: A randomly selected subset of participants (376 cases and 982 controls) that had enrolled in a larger case-control study conducted in six distinct geographic regions of the United States were examined. DNAs were genotyped for the 22 SNP variants in OncoVue and combined with personal factors to calculate the risk scores for the individual participants. DNAs were also genotyped for the following GWAS SNPs: rs2981582 (FGFR2), rs3817198 (LSP1), rs889312 (MAP3K), rs4415084 (MRPS30), rs13281615 (POU5F1P1), rs13387042 (TNP1), and rs3803662 (TOX3, formerly TNRCR9). Association of individual GWAS SNP genotypes with breast cancer risk was evaluated by calculating odds ratios (ORs). Assuming independent contribution of each SNP to risk, a combined GWAS risk score was calculated using a multiplicative model. Positive likelihood ratios (PLRs) were calculated using a risk threshold of 1.5-fold the control population mean risk to evaluate the proportion of individuals placed at elevated risk by OncoVue compared to the combined GWAS risk scores.Results: OncoVue exhibited significant ability to stratify risk at the 1.5-fold mean with a PLR of 2.2 and at a risk level of 2.5-fold mean the PLR increased to 5.0. In analyses of individual GWAS SNPs, statistically significant associations with breast cancer were identified for homozygous carriers of the rare allele for the FGFR2, MAP3K and TOX3 genes. However, the PLR for the combined GWAS risk scores at 1.5-fold mean was 1.0 indicating no ability to discriminate risk in this study population.Conclusions: In this case-control population OncoVue effectively stratified risk by accurately assigning elevated risk to breast cancer cases. In the same population, a combined risk score produced from seven GWAS SNPs did not effectively stratify risk. These results indicate that the OncoVue model has clinical utility for identifying elevated risk women who might benefit from additional screening and prevention. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 3177.

A framework for managing wandering and preventing elopement.

A framework aids choice of interventions to manage wandering and prevent elopement in consideration of associated risks and mobility needs of wanderers. A literature review, together with research results, published wandering tools, clinical reports, author clinical experience, and consensus-based judgments was used to build a decision-making framework. Referencing a published definition of wandering and originating a clinical description of problematic wandering, authors introduce a framework comprising (1) wandering and related behaviors; (2) goals of wandering-specific care, (3) interpersonally, technologically, and policy-mediated wandering interventions, and (4) estimates of relative frequencies of wandering behaviors, magnitudes of elopement risk, and restrictiveness of strategies. Safeguarding wanderers from elopement risk is rendered person-centered and humane when goals of care guide intervention choice. Despite limitations, a reasoned, systematized approach to wandering management provides a basis for tailoring a specialized program of care. The need for framework refinement and related research is emphasized.

Abstract CN07-03: Discriminatory accuracy from Single Nucleotide Polymorphisms in models of absolute breast cancer risk

Abstract CN07-03 One purpose for seeking single nucleotide polymorphisms (SNPs) that are associated with disease is to improve models for projecting individualized disease risk. Seven SNPs have recently been confirmed to be associated with breast cancer. I used published estimates of relative risks and allele frequencies to calculate how much these SNPs could improve discriminatory accuracy measured as the area under the receiver operating characteristic curve (AUC). A model with these seven SNPs (AUC = 0.574 ) and a hypothetical model with 14 such SNPs (AUC = 0.604) have less discriminatory accuracy than a model, the National Cancer Institute’s Breast Cancer Risk Assessment Tool (BCRAT), which is based on ages at menarche and at first live birth, family history of breast cancer, and history of breast biopsy examinations (AUC = 0.607). Adding the seven SNPs to BCRAT improved discriminatory accuracy to an AUC of 0.632, which was, however, less than the improvement from adding mammographic density. Thus, these seven SNPs improve the discriminatory accuracy of BCRAT only modestly. I used other criteria to compare BCRAT with a model that added the seven SNPs to BCRAT. These criteria included the proportion of cases in the portion of the population with the highest 90% of risk, the expected losses when using risk models to decide which women should be given a mammogram, and the expected losses when using a risk model to decide which women should take tamoxifen to prevent breast cancer. The seven SNPs provided very little improvement over BCRAT for any of these applications. Hundreds of SNPs would be required to achieve high discriminatory accuracy. Citation Information: Cancer Prev Res 2008;1(7 Suppl):CN07-03.

Discriminatory Accuracy From Single-Nucleotide Polymorphisms in Models to Predict Breast Cancer Risk

One purpose for seeking common alleles that are associated with disease is to use them to improve models for projecting individualized disease risk. Two genome-wide association studies and a study of candidate genes recently identified seven common single-nucleotide polymorphisms (SNPs) that were associated with breast cancer risk in independent samples. These seven SNPs were located in FGFR2, TNRC9 (now known as TOX3), MAP3K1, LSP1, CASP8, chromosomal region 8q, and chromosomal region 2q35. I used estimates of relative risks and allele frequencies from these studies to estimate how much these SNPs could improve discriminatory accuracy measured as the area under the receiver operating characteristic curve (AUC). A model with these seven SNPs (AUC = 0.574) and a hypothetical model with 14 such SNPs (AUC = 0.604) have less discriminatory accuracy than a model, the National Cancer Institute's Breast Cancer Risk Assessment Tool (BCRAT), that is based on ages at menarche and at first live birth, family history of breast cancer, and history of breast biopsy examinations (AUC = 0.607). Adding the seven SNPs to BCRAT improved discriminatory accuracy to an AUC of 0.632, which was, however, less than the improvement from adding mammographic density. Thus, these seven common alleles provide less discriminatory accuracy than BCRAT but have the potential to improve the discriminatory accuracy of BCRAT modestly. Experience to date and quantitative arguments indicate that a huge increase in the numbers of case patients with breast cancer and control subjects would be required in genome-wide association studies to find enough SNPs to achieve high discriminatory accuracy.

Accounting for surveyor inconsistency and bias in estimation of tree density from presettlement land survey records

Presettlement land survey records provide baseline data on forest characteristics prior to major European settlement, but questions regarding surveyor bias and methodological consistency have limited confidence in quantitative analyses of this important data source. We propose new correction factors, calculated from bearings, distances, and species of bearing trees, to account for the effects of (i) inconsistency in quadrant configuration, (ii) bearing angle bias, and (iii) species bias on forest density and species composition estimated from presettlement land survey records. Computer simulations confirmed accuracy in random and nonuniform density forests, with moderate bias in very clustered and dispersed forests. A case study of township and quarter-section corners surveyed by the Holland Land Company in western New York demonstrates the potential magnitude of errors caused by surveyor inconsistency/bias in estimation of density and relative species frequency. The influence of nonuniform density, clustering, and dispersal on plotless density estimators remains an important obstacle to quantitative analysis of Presettlement land survey records. However, by accounting for uncertainties regarding surveyor methodology, the proposed correction factors add confidence to conclusions made regarding presettlement forest structure and composition.

"Difficult Patients" in Mental Health Care: A Review

"Difficult Patients" in Mental Health Care: A Review