Correlated Error Terms Research Articles

Myosin‐actin interaction in Dictyostelium cells revealed by GFP‐based strain sensor and validated linear spectral unmixing

Myosin is an actin-based motor protein that is involved in a wide range of cellular motile processes. Although in vitro properties of the myosin-actin interaction have been extensively studied, the interaction in vivo remains poorly understood. Recently, we developed a GFP-based strain sensor termed PriSSM (PRIM-based strain sensor module), by using the proximity imaging (PRIM) technique, which detects spectral changes of two GFP molecules that are in direct contact. Using PriSSM-myosin II fusion proteins, the interaction between myosin II and F-actin can be detected in Dictyostelium cells. In the spectroscopic measurements of PriSSM, to decompose the measured spectra of the cells expressing the sensor proteins into the contributions from the sensor and the background autofluorescence, we applied the linear spectral unmixing approach, which was based on the assumption that the errors at each wavelength were independent. Cellular autofluorescence, however, often includes systematic errors, so that the unmixing procedures might lead to biased estimates. Here, to validate our spectral unmixing procedures, we estimate the possible maximum errors in the fluorescence ratio values that are obtained by unmixing spectra including such systematic errors. This estimation provided a general criterion to validate the results obtained by linear unmixing of spectra including serially correlated error terms. Using the proposed criterion and PriSSM-myosin II fusion proteins, we examined the interaction between myosin II and F-actin in Dictyostelium cells under several different conditions. The spectroscopic results, together with the microscopic observations of the cells expressing the proteins, suggest that the formation of myosin filaments through the tail region has only a slight effect on binding to F-actin but has significant effects on the cortical localization of myosin II.

Modelling opportunity in health under partial observability of circumstances

This paper proposes a behavioural model of inequality of opportunity in health that integrates John Roemer's framework of inequality of opportunity with the Grossman model of health capital and demand for health. The model generates a recursive system of equations for health and lifestyles, which is then jointly estimated by full information maximum likelihood with freely correlated error terms. The analysis innovates by accounting for the presence of unobserved heterogeneity, therefore addressing the partial-circumstance problem, and by extending the examination of inequality of opportunity to health outcomes other than self-assessed health, such as long-standing illness, disability and mental health. The results provide evidence for the existence of third factors that simultaneously influence health outcomes and lifestyle choices, supporting the empirical relevance of the partial-circumstance problem. Accounting for these factors, the paper corroborates that the effect of parental and early circumstances on adult health disparities is paramount. However, the particular set of circumstances that affect each of the analysed health outcomes differs substantially. The results also show that differences in educational opportunities, and in social development in childhood, are crucial determinants of lifestyles in adulthood, which, in turn, shape the observed health inequalities.

Factor structures of the Swedish Version of the RFIPC: Investigating the Validity of Measurements of IBD Patients' Worries and Concerns.

BackgroundWorries and concerns of patients with IBD comprise an important negative factor in their HRQOL. The Rating Form of Inflammatory Bowel Disease Patient Concerns (RFIPC) was developed to describe the nature and degree of the worries and concerns of IBD patients. In the original version, the specific issues of worries are divided into four separate factors. These factors provide useful information about HRQOL and the kind of worries and concerns which are most important to the patient. However, the Swedish version of the RFIPC is often scored using a single sum score, implying that all the specific issues of worries stem from a single general worry factor. The aim of this study was to validate the factor structure of the Swedish version of the RFIPC.MethodsA sample consisting of 195 patients with IBD filled out the RFIPC. Confirmatory factor analysis was performed to examine fit of three hypothesized models of factor structure. Spearman’s correlation and Mann-Whitney analysis were used to follow up the results.ResultsThe single-factor model displayed poor fit indices. The four-factor model marked substantive improvement, but still remains inadequate. The final four-factor model permitting correlated error terms between some items displayed the most adequate fit.ConclusionsThe factorial structure of the RFIPC, as suggested in the original version, was able to be replicated with a slight modification in the Swedish version. The separate factors identified in this structure provide more detailed information about the worries and concerns of IBD patients as these components of worries are different related to HRQOL and general health.

Determinants of Domestic Water Use by Rural Households Without Access to Private Improved Water Sources in Benin: A Seemingly Unrelated Tobit Approach

This paper analyzes the determinants of domestic water use in rural areas. The focus is on households without access to private improved water sources. These households use either only free sources, only purchased sources or a combination of free and purchased sources. We also analyze households’ water use behaviors as a function of water availability by explicitly estimating domestic water use for both rainy and dry seasons. Using a Seemingly Unrelated Tobit approach to simultaneously account for the censored nature of water demand and the correlation of error terms between free and purchased water use equations, we find that purchased water demand is perfectly price inelastic due to water scarcity. The important determinants of water use are household size and composition, access to water sources, wealth and time required for fetching water. Nevertheless, the effects of these determinants vary between household types and seasons, and the policy implications of the findings are discussed.

Performances Of The Full Information Estimators In A Two-Equation Structural Model With Correlated Disturbances

The performances of two full information techniques, Three Stage Least Squares (3SLS) and Full Information Maximum Likelihood (FIML) of simultaneous equation models with correlated disturbance terms are compared with the Ordinary Least Squares (OLS) method in small samples. Comparative performance evaluation of the estimators was done using Average of Estimates, Total Absolute Bias (TAB) of Estimates, Root Mean Squared Error (RMSE) and Sum of Squared Residuals (RSS) of parameter estimates. The results of the Monte Carlo experiment showed that OLS is best with large negative or positive correlation, while 3SLS is best with feebly correlated error terms in the case of replication-based averages. The total absolute biases increase consistently as the sample size increases for OLSwhile FIML estimates reveal no distinct pattern. The magnitudes of the estimates yielded by two estimators, OLS and 3SLS, exhibited fairly consistent reaction to changes in magnitudes and direction of correlations of error terms.

Multivariate SPC for recipe preservation of batch processes

AbstractThe performances of the Hotelling's T2 control chart and the squared prediction error control chart based on the multi‐way principal component analysis are evaluated for monitoring within batch process variation for the purpose of recipe preservation. A nonlinear model for simulated batch process data is provided. The model allows for cross correlation of error terms at a given time period and serial correlation of error terms across time periods. The performance characterizations of the two monitoring schemes are provided for a variety of levels of cross correlation and serial correlation. The impact of the time period at which process shifts occur is also investigated for the monitoring schemes. The T2 control chart is recommended for the cases considered. Copyright © 2009 John Wiley & Sons, Ltd.

Are Tax Havens Good Neighbors? An LDC Perspective

Tax competition and spillover models offer ambiguous predictions of tax haven impacts on non-tax havens. The implications of tax havens for less developed countries (LDCs), in particular, are not well understood and are little studied. This paper investigates the impact of tax havens on foreign direct investment (FDI) in non-tax haven LDCs. We investigate spillover and agglomeration factors by including measures of proximity to the nearest tax haven and the level of FDI inflows in the nearest tax haven. Employing cross sectional data of 115 LDCs from 1990 to 2006, we find evidence of spillovers from tax havens to nearby LDCs. FDI inflows in LDCs are positively and significantly related to FDI inflows in the nearest tax haven. Geographic diffusion has nuanced effects. LDCs at a medium distance to the nearest tax haven have higher levels of FDI than LDCs that are close to a tax haven. On the other hand, LDCs at a medium distance to a tax haven are less influenced by FDI spillovers compared with LDCs at closer proximity. Taken together, our results suggest that tax havens make good regional neighbors, but not good immediate neighbors for LDCs. These findings are robust to several model specifications, including one with spatially correlated error terms..

The short version of the Depression Anxiety Stress Scales (DASS-21): Factor structure in a young adolescent sample

This study explored the factor structure of the short form of the Depression Anxiety Stress Scales (DASS-21; Lovibond & Lovibond, 1995b) in a young adolescent sample. A group of 484 high school students ( Mean age = 13.62 years, Min = 11.83, Max = 15.67 years, 52 % boys) completed the DASS-21. Several models were tested using Confirmatory Factor Analysis. A model consistent with the factor structure of the adult DASS, with correlated error terms, provided good fit to the data. However, correlations among the factors were very high. A ‘quadripartite’ model involving a common ‘Negative Affect’ factor as well as the three specific factors of Depression, Anxiety and Tension/Stress was tested to explain these correlations and was supported by the data. This model suggests that the core symptoms of Depression and Anxiety are similar in adults and adolescents, but the conceptualisation and assessment of Tension/Stress in adolescents needs further refinement.

Community-Level Correlates of Hospitalizations for Persons With Schizophrenia

Community-Level Correlates of Hospitalizations for Persons With Schizophrenia

Participation in marijuana, cocaine and heroin consumption in Australia: a multivariate probit approach

This article investigates factors affecting the participation in marijuana, cocaine and heroin using micro-unit data from an Australian national survey on recreational drugs. Accounting for cross-drug correlation potentially induced by unobserved personal characteristics such as individual tastes and addictive personalities, we estimate a trivariate probit model, where the participation decisions are jointly modelled as a system with correlated error terms. The estimated correlation coefficients are significant across all three drugs. The study provides valuable empirical information on conditional and joint probabilities of drug participation. The multivariate approach is shown to provide better analysis relative to a univariate approach that does not address the endogeneity of all drug participation variables.

3P-258 誤差を含む混合蛍光スペクトルに対するスペクトル分離の有効性の検討(バイオイメージング,第47回日本生物物理学会年会)

3P-258 誤差を含む混合蛍光スペクトルに対するスペクトル分離の有効性の検討(バイオイメージング,第47回日本生物物理学会年会)

Construct validity of the five‐factor Strengths and Difficulties Questionnaire (SDQ) in pre‐, early, and late adolescence

The Strengths and Difficulties Questionnaire (SDQ) is designed to measure psychological adjustment in children and adolescents. Psychometric evaluations of the instrument have shown satisfactory convergent and discriminant validity, while factor analysis studies have shown mixed results across countries. In the present study, the construct validity of the five-factor SDQ is evaluated in a large community sample of Norwegian pre-, early, and late adolescents. The sample consisted of 26,269 children and adolescents (10-19 years) with valid answers on all 25 items of the SDQ self-report. Complete parent/proxy data of respective pre-adolescent children was available for 6,645 cases. A Lisrel approach to Confirmatory Factor Analysis (CFA) was used to evaluate the five-factor model and the presence of a positive construal factor. In the sample of pre-adolescents and their parents/proxies, convergent and discriminant validity was evaluated by a CFA approach to multitrait-multimethods (MTMM). Fit statistics for the hypothesized five-factor model were satisfactory, but introducing correlated error terms for some of the items led to significant model improvement in all age groups. All factor loadings were higher than .30, except for item 11 (good friend). The loadings differed across age groups and differed markedly between the parent/proxy and self-report measures. The MTMM showed that the source of ratings made a difference on the validity of all subscale ratings, with self-reports discriminating more on ratings of emotional and peer problems, and parents/proxies discriminating more on hyperactivity symptoms. A positive construal factor was identified but had a modest effect compared with the original five traits. Results suggested an unclear construct and meaning of the Prosocial behaviour subscale. The results of the present study indicated support for the proposed five-factor structure of the SDQ (Goodman, 2001) across a wide age range (10-19years), including older adolescents and different informants. However, some improvements should be considered to improve internal reliability and conceptual clarity.

Efficacy of Iron Chelation in Reducing Cardiac Iron as Assessed by MRI T2* in Patients with Thalassemia Major

241 thalassemia major patients have had repeated evaluation of cardiac iron assessed by Magnetic Resonance Imaging (MRI) over a median interval of 15 months (range 2.6–72.6). We compared changes in T2* between MRI studies with desferrioxamine (DFO) – (number of patients (n)=31, total MRIs (nMRI)=116), deferiprone (DFP) − (n=41 nMRI=94) and combination of DFO and DFP (Comb) − (n=143 nMRI=347) using repeated measurement analysis with correlated error terms and time varying covariates. Patients were divided into four groups according to their baseline cardiac T2* (Heavy load £ 8 ms, moderate load 8–14, mild 314–20 and normal 320). Table 1 shows the overall assessment excluding patients on DFX. These were not included in that assessment as the total period of exposure was statistically significantly less than that of the other regimes. Analysis was therefore performed using student T test to assess the rate of change between the first and second MRI in the T2* values in patients with comparable cardiac siderosis according to each chelation regime adjusted for overall time of exposure (Table 2). With linear regression analysis (Table3) we compared the effect of DFO to the other three regimes in the annual rate of increasing cardiac T2*. The results have been adjusted for baseline T2* and time of exposure to therapy. Both DFP and Comb regimes are superior to DFO in reducing cardiac siderosis. This indicates that over one year DFP and Comb regimes will have a greater increase in T2* than that achieved by DFO. In addition, Comb seems to be superior to DFX as it would increase the T2* by 2ms/year above that which can be achieved by DFX (p=0.007). DFP achieves 1.7ms/year above the annual improvement with DFX but the difference is not statistically significant. The estimated difference in annual improvement of T2* between Comb and DFP is 0.33ms/year (p=0.07) These data confirm that which is seen in clinical practice according to the chelation regimes used. It is clear that the combination of DFO and DFP is the most rapid regime for reducing cardiac iron and seems to be effective at all levels of cardiac siderosis. The ability to assess tissue iron in the heart is extremely clinically valuable and allows preemptive intervention in order to reduce cardiac morbidity and mortality by the selection of the most appropriate chelation therapy according to the MRI findings.Table1 Annual estimated mean change in T2* according to severity of cardiac siderosisRegimeHeavyModerateMildΔT2*pΔT2*pΔT2*pDFO0.61n.s1.06n.s.−1.5n.s.DFP0.55<0.0012.8<0.0013.4<0.001Comb1.4<0.0013.5<0.0012.6<0.001Table 2 Annual estimated mean change in T2* according to severity of cardiac siderosisRegimeHeavyModerateMildΔT2*PΔT2*pΔT2*pDFO n= 73 tm*= 230.730.051.070.090.90.4DFP n= 53 tm=18.51.950.143.20.00453.90.06Comb n= 152 tm=21.21.98<0.0014.4<0.0015.70.0025DFX n=96 tm=14.9−0.510.41−0.670.44.20.23*tm= mean time (in months) between MRI studiesTable 3Mean estimated difference in T2*Standard ErrorpDFP v. DFO2.10.990.033Comb v DFO2.40.69<0.001DFX v DFO0.440.820.6

Recovery and Replication of Internalizing and Externalizing Dimensions Within the Personality Assessment Inventory

In this study, we examined the internal structure of 13 Personality Assessment Inventory (PAI; Morey, 1991, 2007) scales in a corrections sample (N = 1,099). Previous findings regarding the PAI internal structure have been somewhat inconsistent. We investigated the utility of a 2-dimensional model comprised of internalization and externalization to organize the 11 PAI clinical scales and 2 additional scales, Suicidal Ideation and Aggression. We randomly divided the sample, and a factor analysis revealed a 2-dimensional model representing internalization and externalization. Confirmatory factor analyses conducted with an independent subsample revealed acceptable fit when the model was revised to include correlated error terms between mood and anxiety disorder scales. The revised model exhibited acceptable fit when cross-validated, had better fit than a 1-dimension model, and demonstrated preliminary construct validity in relation to extratest variables.

Estimating the marginal costs of airport operation using multivariate time series models with correlated error terms

This paper explores insights about marginal airport costs that can be gained by analysing labour inputs and their variability. Based on hourly cost and traffic data for the airport of Helsinki, a multivariate time series approach is used incorporating correlated error terms to account for random shocks such as delays. We found for most airport services a linear relationship between labour input and aircraft movements, except for producing passenger services for international departing flights where a cubic cost relationship was estimated. The findings are comparable with earlier studies for US airports.

Factor invariance between genders of the Wechsler Intelligence Scale for Children – Fourth edition

The purpose of this study was to test measurement invariance of the WISC-IV factorial structure between genders. Both 10 and 15 subtest sets were tested on a nationally-representative sample of 2200 children (males N = 1100; females N = 1100). Results from multisample analyses supported partial measurement invariance. Except for a few subtle discrepancies involving correlated error terms, the hypothesized model described the data for both sexes. Overall factor patterns, loadings, unique variances, and factor covariances of the WISC-IV generally did not vary with gender.

Dynamic incentives and retirement

This paper examines multi-period compensation contracts when retirement is anticipated. Short-term contracts in long-term employment relationships are equivalent to a long-term renegotiation-proof contract. The dynamic of incentive rates is determined by (i) how and in which periods managerial effort affects the contractible performance measures; and by (ii) the time-series correlation of error terms in performance reports. The model explains why long-term investments can decrease while incentive rates increase as managers approach retirement. Earnings persistence is negatively associated to earnings-based incentive rates but, towards retirement, high earnings persistence implies increasing earnings-based incentive rates.

Prescription Drug Coverage and Effects on Drug Expenditures among Elderly Medicare Beneficiaries

To identify determinants of drug coverage among elderly Medicare beneficiaries and to investigate the impact of drug coverage on drug expenditures with and without taking selection bias into account. The primary data were from the 2000 Medicare Current Beneficiary Survey (MCBS) Cost and Use file, linked to other data sources at the county or state-level that provided instrumental variables. Community-dwelling elderly Medicare beneficiaries who completed the survey were included in the study (N=7,525). A probit regression to predict the probability of having drug coverage and the effects of drug coverage on drug expenditures was estimated by a two-part model, assuming no correlation across equations. In addition, the discrete factor model estimated choice of drug coverage and expenditures for prescription drugs simultaneously to control for self-selection into drug coverage, allowing for correlation of error terms across equations. Findings indicated that unobservable characteristics leading elderly Medicare beneficiaries to purchase drug coverage also lead them to have higher drug expenditures on conditional use (i.e., adverse selection), while the same unobservable factors do not influence their decisions whether to use any drugs. After controlling for potential selection bias, the probability of any drug use among persons with drug coverage use was 4.5 percent higher than among those without, and drug coverage led to an increase in drug expenditures of $308 among those who used prescription drugs. Given significant adverse selection into drug coverage before the implementation of the Medicare Prescription Drug Improvement and Modernization Act, it is essential that selection effects be monitored as beneficiaries choose whether or not to enroll in this voluntary program.

Testing for random effects in panel models with spatially correlated disturbances

In the empirical analysis of panel data the Breusch–Pagan (BP) statistic has become a standard tool to infer on unobserved heterogeneity over the cross‐section. Put differently, the test statistic is central to discriminate between the pooled regression and the random effects model. Conditional versions of the test statistic have been provided to immunize inference on unobserved heterogeneity against random time effects or patterns of spatial error correlation. Panel data models with spatially correlated error terms are typically set out under the presumption of some known adjacency matrix parameterizing the correlation structure up to a scaling factor. This paper delivers a bootstrap scheme to generate critical values for the BP statistic allowing robust inference under misspecification of the adjacency matrix. Moreover, asymptotic results are derived for the case of a finite cross‐section and infinite time dimension. Finite sample simulations show that misspecification of spatial covariance features could lead to large size distortions, while the robust bootstrap procedure retains asymptotic validity.

Unidimensionality, asymmetry and (S,s) rules in labour demand

We analyse the conditions under which an (S,s) rule may be implemented in the case of labour demand. The (S,s) rule implies a specific ordering of choices: downward adjustment, nonadjustment and upward adjustment with the decision of inaction lying crucially in the middle. This requires an exact negative relation between the choice-specific error terms. The particular ordering of choices implied may be estimated by an ordered probit. We test the (S,s) rule nesting the ordered probit within a multinomial model with correlated error terms. The restriction to a univariate error distribution is rejected by the data.