Asymptotic robustness in multi-sample analysis of multivariate linear relations

Standard methods for the analysis of linear latent variable models oftenrely on the assumption that the vector of observed variables is normallydistributed. This normality assumption (NA) plays a crucial role inassessingoptimality of estimates, in computing standard errors, and in designinganasymptotic chi-square goodness-of-fit test. The asymptotic validity of NAinferences when the data deviates from normality has been calledasymptoticrobustness. In the present paper we extend previous work on asymptoticrobustnessto a general context of multi-sample analysis of linear latent variablemodels,with a latent component of the model allowed to be fixed across(hypothetical)sample replications, and with the asymptotic covariance matrix of thesamplemoments not necessarily finite. We will show that, under certainconditions,the matrix $\Gamma$ of asymptotic variances of the analyzed samplemomentscan be substituted by a matrix $\Omega$ that is a function only of thecross-product moments of the observed variables. The main advantage of thisis thatinferences based on $\Omega$ are readily available in standard softwareforcovariance structure analysis, and do not require to compute samplefourth-order moments. An illustration with simulated data in the context ofregressionwith errors in variables will be presented.

Asymptotic robust inferences in the analysis of mean and covariance structures

Structural equation models are widely used in economic, socialand behavioral studies to analyze linear interrelationships amongvariables, some of which may be unobservable or subject to measurementerror. Alternative estimation methods that exploit different distributionalassumptions are now available. The present paper deals with issues ofasymptotic statistical inferences, such as the evaluation of standarderrors of estimates and chi--square goodness--of--fit statistics,in the general context of mean and covariance structures. The emphasisis on drawing correct statistical inferences regardless of thedistribution of the data and the method of estimation employed. A(distribution--free) consistent estimate of $\Gamma$, the matrix ofasymptotic variances of the vector of sample second--order moments,will be used to compute robust standard errors and a robust chi--squaregoodness--of--fit squares. Simple modifications of the usual estimateof $\Gamma$ will also permit correct inferences in the case of multi--stage complex samples. We will also discuss the conditions under which,regardless of the distribution of the data, one can rely on the usual(non--robust) inferential statistics. Finally, a multivariate regressionmodel with errors--in--variables will be used to illustrate, by meansof simulated data, various theoretical aspects of the paper.

Scaled and adjusted restricted tests in multi-sample analysis of moment structures

We extend to score, Wald and difference test statistics the scaled and adjusted corrections to goodness-of-fit test statistics developed in Satorra and Bentler (1988a,b). The theory is framed in the general context of multisample analysis of moment structures, under general conditions on the distribution of observable variables. Computational issues, as well as the relation of the scaled and corrected statistics to the asymptotic robust ones, is discussed. A Monte Carlo study illustrates thecomparative performance in finite samples of corrected score test statistics.

Regulation of the expression of Fit insect toxin locus genes in the root-associated biocontrol pseudomonad CHA0

The root-colonizing Pseudomonas fluorescens strain CHA0 is a biocontrol agent of soil-borne plant diseases caused by fungal and oomycete pathogens. Remarkably, this plant-beneficial pseudomonad is also endowed with potent insecticidal activity that depends on the production of a large protein toxin termed Fit (for P. fluorescens insecticidal toxin). In our present work, the genomic locus encoding the P. fluorescens insect toxin is subjected to a detailed molecular analysis. The Fit toxin gene fitD is flanked upstream by the fitABC genes and downstream by the fitE gene that encode the ABC transporter, membrane fusion, and outer membrane efflux components of a type I protein secretion system predicted to function in toxin export. The fitF, fitG, and fitH genes located downstream of fitE code for regulatory proteins having domain structures typical of signal transduction histidine kinases, LysR-type transcriptional regulators, and response regulators, respectively. The role of these insect toxin locus-associated control elements is being investigated with mutants defective for the regulatory genes and with GFP-based reporter fusions to putative promoter regions upstream of the transporter genes fitA and fitE, the toxin gene fitD, and the regulatory genes fitF and fitH. Our preliminary findings suggest that the three regulators interact with known global regulators of biocontrol factor expression to control Fit toxin expression and secretion.

Minimum distance estimation of stationary and non-stationary ARFIMA processes

A new parametric minimum distance time-domain estimator for ARFIMA processes is introduced in this paper. The proposed estimator minimizes the sum of squared correlations of residuals obtained after filtering a series through ARFIMA parameters. The estimator iseasy to compute and is consistent and asymptotically normally distributed for fractionallyintegrated (FI) processes with an integration order d strictly greater than -0.75. Therefore, it can be applied to both stationary and non-stationary processes. Deterministic components are also allowed in the DGP. Furthermore, as a by-product, the estimation procedure provides an immediate check on the adequacy of the specified model. This is so because the criterion function, when evaluated at the estimated values, coincides with the Box-Pierce goodness of fit statistic. Empirical applications and Monte-Carlo simulations supporting the analytical results and showing the good performance of the estimator in finite samples are also provided.

Country effects in ISSP-1993 environmental data: Comparison of SEM approaches

Structural equation models (SEM) are commonly used to analyze the relationship between variables some of which may be latent, such as individual ``attitude'' to and ``behavior'' concerning specific issues. A number of difficulties arise when we want to compare a large number of groups, each with large sample size, and the manifest variables are distinctly non-normally distributed. Using an specific data set, we evaluate the appropriateness of the following alternative SEM approaches: multiple group versus MIMIC models, continuous versus ordinal variables estimation methods, and normal theory versus non-normal estimation methods. The approaches are applied to the ISSP-1993 Environmental data set, with the purpose of exploring variation in the mean level of variables of ``attitude'' to and ``behavior''concerning environmental issues and their mutual relationship across countries. Issues of both theoretical and practical relevance arise in the course of this application.

A joint back calculation model for the imputation of the date of HIV infection in a prevalent cohort.

In studies of the natural history of HIV-1 infection, the time scale of primary interest is the time since infection. Unfortunately, this time is very often unknown for HIV infection and using the follow-up time instead of the time since infection is likely to provide biased results because of onset confounding. Laboratory markers such as the CD4 T-cell count carry important information concerning disease progression and can be used to predict the unknown date of infection. Previous work on this topic has made use of only one CD4 measurement or based the imputation on incident patients only. However, because of considerable intrinsic variability in CD4 levels and because incident cases are different from prevalent cases, back calculation based on only one CD4 determination per person or on characteristics of the incident sub-cohort may provide unreliable results. Therefore, we propose a methodology based on the repeated individual CD4 T-cells marker measurements that use both incident and prevalent cases to impute the unknown date of infection. Our approach uses joint modelling of the time since infection, the CD4 time path and the drop-out process. This methodology has been applied to estimate the CD4 slope and impute the unknown date of infection in HIV patients from the Swiss HIV Cohort Study. A procedure based on the comparison of different slope estimates is proposed to assess the goodness of fit of the imputation. Results of simulation studies indicated that the imputation procedure worked well, despite the intrinsic high volatility of the CD4 marker.

Equivalence of paper and pencil vs internet forms of the ZKPQ-50-CC in Spanish and French samples

This study was designed to check for the equivalence of the ZKPQ-50-CC (Spanish and French versions) through Internet on-line (OL) and paper and pencil (PP) answer format. Differences in means and devia- tions were significant in some scales, but effect sizes are minimal except for Sociability in the Spanish sample. Alpha reliabilities are also very similar in both versions with no significant differences between formats. A robust factorial structure was found for the two formats and the average congruency coefficients were 0.98. The goodness-of-fit indexes obtained by confirmatory factorial analysis are very similar to those obtained in the ZKPQ-50-CC validation study and they do not differ between the two formats. The multi-group analysis confirms the equivalence among the OL-PP formats in both countries. These results in general support the validity and reliability of the Internet as a method in investigations using the ZKPQ-50-CC.

Validation of the 34-item Supportive Care Needs Survey and 8-item Breast module French versions (SCNS-SF34-Fr and SCNS-BR8-Fr) in breast cancer patients.

This study aimed to assess the psychometric robustness of the French version of the Supportive Care Needs Survey and breast cancer (BC) module (SCNS-SF34-Fr and SCNS-BR8-Fr). Breast cancer patients were recruited in two hospitals (in Paris, France and Lausanne, Switzerland) either in ambulatory chemotherapy or radiotherapy, or surgery services. They were invited to complete the SCNS-SF34-Fr and SCNS-BR8-Fr as well as quality of life and patient satisfaction questionnaires. Three hundred and eighty-four (73% response rate) BC patients returned completed questionnaires. A five-factor model was confirmed for the SCNS-SF34-Fr with adequate goodness-of-fit indexes, although some items evidenced content redundancy, and a one-factor was identified for the SCNS-BR8-Fr. Internal consistency and test-retest estimates were satisfactory for most scales. The SCNS-SF34-Fr and SCNS-BR8-Fr scales demonstrated conceptual differences with the quality of life and satisfaction with care scales, highlighting the specific relevance of this assessment. Different levels of needs could be differentiated between groups of BC patients in terms of age and level of education (P < 0.001). The SCNS-SF34-Fr and SCNS-BR8-Fr present adequate psychometric properties despite some redundant items. These questionnaires allow for the crucial endeavour to design appropriate care services according to BC patients' characteristics.

The data treatment dependent variability of U-Pb zircon ages obtained using mono-collector, sector field, laser ablation ICP-MS

U-Pb dating of zircons by laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) is a widely used analytical technique in Earth Sciences. For U-Pb ages below 1 billion years (1 Ga), Pb-206/U-238 dates are usually used, showing the least bias by external parameters such as the presence of initial lead and its isotopic composition in the analysed mineral. Precision and accuracy of the Pb/U ratio are thus of highest importance in LA-ICPMS geochronology. We consider the evaluation of the statistical distribution of the sweep intensities based on goodness-of-fit tests in order to find a model probability distribution fitting the data to apply an appropriate formulation for the standard deviation. We then discuss three main methods to calculate the Pb/U intensity ratio and its uncertainty in the LA-ICPMS: (1) ratio-of-the-mean intensities method, (2) mean-of-the-intensity-ratios method and (3) intercept method. These methods apply different functions to the same raw intensity vs. time data to calculate the mean Pb/U intensity ratio. Thus, the calculated intensity ratio and its uncertainty depend on the method applied. We demonstrate that the accuracy and, conditionally, the precision of the ratio-of-the-mean intensities method are invariant to the intensity fluctuations and averaging related to the dwell time selection and off-line data transformation (averaging of several sweeps); we present a statistical approach how to calculate the uncertainty of this method for transient signals. We also show that the accuracy of methods (2) and (3) is influenced by the intensity fluctuations and averaging, and the extent of this influence can amount to tens of percentage points; we show that the uncertainty of these methods also depends on how the signal is averaged. Each of the above methods imposes requirements to the instrumentation. The ratio-of-the-mean intensities method is sufficiently accurate provided the laser induced fractionation between the beginning and the end of the signal is kept low and linear. We show, based on a comprehensive series of analyses with different ablation pit sizes, energy densities and repetition rates for a 193 nm ns-ablation system that such a fractionation behaviour requires using a low ablation speed (low energy density and low repetition rate). Overall, we conclude that the ratio-of-the-mean intensities method combined with low sampling rates is the most mathematically accurate among the existing data treatment methods for U-Pb zircon dating by sensitive sector field ICPMS.

CO2-response function of radiation use efficiency in rice for climate change scenarios

The objective of this work was to evaluate a generalized response function to the atmospheric CO2 concentration [f(CO2)] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (R²), and the root mean square error (RMSE). The f(CO2) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO2 emissions for the next generation of climate scenarios for the 21st century.

Phylogenetic position of Fit insect toxin producing pseudomonads

Fit produced by Pseudomonas fluorescens CHA0 is a novel insect toxin in root colonizing pseudomonads, of which a homologue is described in Photorhabdus species.However, occurrence and abundance of insect pathogenicity in plant-associated pseudomonads is still unclear. An extensive screening outside the P. fluorescens complex identified strains of Pseudomonas chlororaphis as further Fit toxin producing candidates. Sequences of five different P. chlororaphis strains generated in this study were used to reconstruct the evolutionary history of the Fit toxin gene and to analyse its mode of evolution. We found that P. chlororaphis is closely associated with a small subgroup of 2,4-diacetylphloroglucinol and pyoluteorin- producing pseudomonads, both when analyzing four housekeeping genes and the nucleotide sequences for the Fit toxin gene. Additionally, we identified purifying selection to be the predominant mode of Fit toxin evolution.

Translation and psychometric evaluation of a French version of the Readiness for Hospital Discharge Scale.

AIMS AND OBJECTIVES: To evaluate the reliability and the factor structure of the Readiness for Hospital Discharge Scale - French version. BACKGROUND: The patient's perspective is essential when assessing risk for adverse events at hospital discharge. Developed in the USA, the Readiness for Hospital Discharge Scale is the only instrument that measures an individual's self-perception of readiness before leaving the hospital. A French version of the Readiness for Hospital Discharge Scale was developed and validated. DESIGN: Cross-sectional study. METHODS: A convenience sample of 265 older inpatients from four medical units was selected. The translation and cultural adaptation of the scale involved experts in gerontology and the French language and included back translation. The items were semantically evaluated and pretested in 10 older inpatients. The scale's psychometric properties were internally validated by using confirmatory and exploratory factor analyses. Reliability was assessed by examining the internal consistency of its items. RESULTS: Goodness-of-fit indices of the confirmatory factor analyses were not adequate, but reliability was acceptable (Cronbach's α = 0·80). Exploratory factor analysis of the French version provided results close to those described for the English version, with three similar subscales (physical and emotional readiness, coping with medical treatment and personal care), whereas the initially described Expected Support subscale was not identified in the French version. CONCLUSION: The Readiness for Hospital Discharge Scale - French version appears to be partially consistent with its original English version, but requires additional adaptation to fully take into account the Swiss context and culture to achieve its original aim. RELEVANCE TO CLINICAL PRACTICE: Assessing patient readiness for hospital discharge before leaving hospital could help nurses to improve the discharge planning process and achieve better patient preparedness and care coordination.

Validation of an instrument to evaluate quality of life in the aging population: WHOQOL-AGE.

BACKGROUND: There is a need for short, specific instruments that assess quality of life (QOL) adequately in the older adult population. The aims of the present study were to obtain evidence on the validity of the inferences that could be drawn from an instrument to measure QOL in the aging population (people 50+ years old), and to test its psychometric properties. METHODS: The instrument, WHOQOL-AGE, comprised 13 positive items, assessed on a five-point rating scale, and was administered to nationally representative samples (n = 9987) from Finland, Poland, and Spain. Cronbach's alpha was employed to assess internal consistency reliability, whereas the validity of the questionnaire was assessed by means of factor analysis, graded response model, Pearson's correlation coefficient and unpaired t-test. Normative values were calculated across countries and for different age groups. RESULTS: The satisfactory goodness-of-fit indices confirmed that the factorial structure of WHOQOL-AGE comprises two first-order factors. Cronbach's alpha was 0.88 for factor 1, and 0.84 for factor 2. Evidence supporting a global score was found with a second-order factor model, according to the goodness-of-fit indices: CFI = 0.93, TLI = 0.91, RMSEA = 0.073. Convergent validity was estimated at r = 0.75 and adequate discriminant validity was also found. Significant differences were found between healthy individuals (74.19 ± 13.21) and individuals with at least one chronic condition (64.29 ± 16.29), supporting adequate known-groups validity. CONCLUSIONS: WHOQOL-AGE has shown good psychometric properties in Finland, Poland, and Spain. Therefore, considerable support is provided to using the WHOQOL-AGE to measure QOL in older adults in these countries, and to compare the QOL of older and younger adults.

Dry months in the agricultural region of Ribeirão Preto, state of São Paulo-Brazil: an study based on the extreme value theory

The application of the Extreme Value Theory (EVT) to model the probability of occurrence of extreme low Standardized Precipitation Index (SPI) values leads to an increase of the knowledge related to the occurrence of extreme dry months. This sort of analysis can be carried out by means of two approaches: the block maxima (BM; associated with the General Extreme Value distribution) and the peaks-over-threshold (POT; associated with the Generalized Pareto distribution). Each of these procedures has its own advantages and drawbacks. Thus, the main goal of this study is to compare the performance of BM and POT in characterizing the probability of occurrence of extreme dry SPI values obtained from the weather station of Ribeirão Preto-SP (1937-2012). According to the goodness-of-fit tests, both BM and POT can be used to assess the probability of occurrence of the aforementioned extreme dry SPI monthly values. However, the scalar measures of accuracy and the return level plots indicate that POT provides the best fit distribution. The study also indicated that the uncertainties in the parameters estimates of a probabilistic model should be taken into account when the probability associated with a severe/extreme dry event is under analysis.