Application of canonical correlational analysis to learning data.

Considers the application of Hotelling's canonical correlation analysis to certain problems of learning, such as (1) prediction of learning from external measures, (2) efficiency of learning indices as predictors of academic grades, (3) the extent to which different sets of learning scores share the same function, and (4) changes in the factorial structure of learning as practice continues. Analyses of the published data using this statistical method reveal that there is a considerable amount of improvement in predictive efficiency if learning is treated in multivariate terms. An important methodological point is the finding that in classical eyelidconditioning experiments, the Ss should be matched in terms of their reflex sensitivity to light and puff. It is also felt that canonical analysis may serve as an alternative method of studying the nature and extent of change in ability patterns as improvement occurs in a learning task. (51 ref.) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Non-Hodgkin's lymphomas of the salivary gland: analysis of prognostic factors in 28 cases

Primary malignant lymphomas of the major salivary glands are rare and usually arise in the parotid gland (2% of all neoplastic disorders). In this report clinical records of 28 cases of NHL of salivary glands (27 in the parotid gland and one in the submandibular gland) are reviewed and problems related to diagnosis and management strategies are discussed. The 5-year overall survival rate was 72% and did non differ from the survival of other NHL of the head and neck. Statistical evaluation of prognostic factors (age, histology, clinical stage, grading, bulky and surgical approach--biopsy versus parotidectomy), are presented. Analysis of these factors showed that prognosis was not influenced by age, histology, clinical stage and grading of disease. Poor survival was significantly correlated to bulky lesions (tumor size greater than 6 cm). In our experience surgical treatment did not significantly affect survival rate. It is concluded that diagnostic surgical procedures in case of suspected NHL of the parotid gland are fine needle aspiration biopsy. (FNAB) or incisional biopsy. The treatment of choice is radiotherapy associated with chemiotherapy in cases of localized-bulky or disseminated disease.     

Fitting intracranial self-stimulation data with growth models.

Until now, the problem of fitting self-stimulation rate-frequency functions has been dealt with by using linear models applied to the linear portion of the empirical curve. In this article, an alternative procedure is presented, together with three sigmoid growth models that seem to accurately fit rate-frequency data. From any of these models, it is possible to compute the two indices of stimulation efficacy in use in the parametric study of brain stimulation reward (M?? and θ?), in addition to the inflection point of the curve, which can be used as an alternative to M??. Important relations allowing initial estimation of each parameter are provided, allowing use of computer programs derived from the Gauss-Newton algorithm for nonlinear regression. The considerations relevant to the choice of a nonlinear model are discussed in terms of each efficacy index. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Application of random-effects pattern-mixture models for missing data in longitudinal studies.

Random-effects regression models have become increasingly popular for analysis of longitudinal data. A key advantage of the random-effects approach is that it can be applied when subjects are not measured at the same number of timepoints. In this article we describe use of random-effects pattern-mixture models to further handle and describe the influence of missing data in longitudinal studies. For this approach, subjects are first divided into groups depending on their missing-data pattern and then variables based on these groups are used as model covariates. In this way, researchers are able to examine the effect of missing-data patterns on the outcome (or outcomes) of interest. Furthermore, overall estimates can be obtained by averaging over the missing-data patterns. A psychiatric clinical trials data set is used to illustrate the random-effects pattern-mixture approach to longitudinal data analysis with missing data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Introduction to functional data analysis.

Psychologists and behavioural scientists are increasingly collecting data that are drawn from continuous underlying processes. We describe a set of quantitative methods, Functional Data Analysis (FDA), which can answer a number of questions that traditional statistical approaches cannot. These methods are applicable for analyzing many datasets that are common in experimental psychology, including time series data, repeated measures, and data distributed over time or space as in neuroimaging experiments. The primary advantage of FDA is that it allows the researcher to ask questions about when in a time series differences may exist between two or more sets of observations. We discuss functional correlations, principal components, the derivatives of functional curves, and analysis of variances models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Application of form features in digital cell analysis of non-Hodgkin's lymphomas

The form of a biological cell nucleus can be characterized by the well-known circularity factor, which is derived from the area of an object and its circumference. More sophisticated form features are introduced, which are calculated from the curvature of an object ("bending energy") or from invariant moments. To investigate the sensitivity of the various form features on controlled changes of form and the behaviour under rotation and scaling, algebraic curves similar to the form of real nucleus profiles are generated. Analysis of the shape characteristics of biological cells requires an extraction of the boundaries of the nuclei. This was performed by an edge detection algorithm using eight gradient masks followed by a contour tracing procedure with feedback. The suitability of the introduced form features for classification of different nucleus profiles of non-Hodgkin's lymphomas (NHL) was tested using a Bayes classifier.     

The prognostic significance of sialyl-Tn antigen in women treated with breast carcinoma treated with adjuvant chemotherapy

BACKGROUND: Sialyl-Tn (STn) represents an aberrantly glycosylated mucin epitope that is expressed in breast carcinoma and other adenocarcinomas and is an important factor in the development of novel immunotherapeutic approaches. The primary aim of the current study was to investigate the influence of STn expression on the prognoses of patients with breast carcinoma. METHODS: A cohort of 207 women diagnosed with invasive breast carcinoma who were treated with anthracycline-containing adjuvant chemotherapy and were enrolled in a randomized clinical trial were studied. Expression of STn was determined by an immunohistochemical procedure in which the B72.3 monoclonal antibody was used. Kaplan-Meier and Cox proportional regression survival analyses were used to compare low STn and high STn patients. RESULTS: Forty-eight (23%) of the 207 specimens demonstrated high STn staining (>25% cells were immunoreactive). During a median follow-up of 5 years, high STn patients had worse disease free survival than low STn patients (55% vs. 74%, respectively; P = 0.03). High STn expression was significantly associated with age (P = 0.04) but not with other conventional prognostic markers. In multivariate analysis using the Cox regression model, high STn emerged as an independent prognostic indicator for disease free survival (hazard ratio [HR], 2.02; 95% confidence interval [CI], 1.09-3.73) and for overall survival (HR, 2.16; 95% CI, 0.95-4.92). CONCLUSIONS: The results of this study suggest that STn may be a valuable marker for identifying women at high risk of developing recurrent breast carcinoma who may be candidates for trials investigating new therapies in combination with standard adjuvant therapy.     

A comparison of three methods of analysis for age-period-cohort models with application to incidence data on non-Hodgkin''s lymphoma

Solution structures and hydrogen exchange characteristics of ligand-RNA aptamer and ligand-DNA aptamer complexes have been solved within the past year. The ligands range from cofactors to amino acids, nucleotides, aminoglycoside antibiotics and peptides that are targeted by the nucleic acid aptamers with high specificity and affinity. The structural and dynamics studies provide insights into the principles, patterns and diversity associated with nucleic acid architecture, molecular recognition and the adaptive binding that takes place upon complex formation. These new results provide opportunities for structure-based drug design strategies relevant to therapeutic intervention.     

Application of hierarchical linear models to assessing change.

Recent advances in the statistical theory of hierarchical linear models should enable important breakthroughs in the measurement of psychological change and the study of correlates of change. A two-stage model of change is proposed here. At the first, or within-subject stage, an individual's status on some trait is modeled as a function of an individual growth trajectory plus random error. At the second, or between-subjects stage, the parameters of the individual growth trajectories vary as a function of differences between subjects in background characteristics, instructional experiences, and possible experimental treatments. This two-stage conceptualization, illustrated with data on Head Start children, allows investigators to model individual change, predict future development, assess the quality of measurement instruments for distinguishing among growth trajectories, and study systematic variation in growth trajectories as a function of background characteristics and experimental treatments. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Diagnostic and prognostic value of interleukin-6 in malignant non-Hodgkin's lymphomas

Sixty six patients with non-Hodgkin's lymphomas (NHL) were studied, interleukin-6 (IL-6) was revealed in the blood sera of 33 patients. IL-6 was revealed more frequently in patients with high-grade malignant (p < 0.05) than in those with low-grade malignancy. The largest group of IL-6 positive patients included NHL patients with diffuse large B-cell lymphoma and angioimmunoblastic lymphoma. The marked relationship was found between the serum IL-6 levels and the stage of disease: the serum IL-6 level was significantly lower in untreated patients with Stages II and III disease than in those with end-stage (IV) NHL. IL-6 significantly decreased upon remission, comparable with its level before the initiation of treatment. Analysing the association of prognosis of disease with the serum IL-6 showed that in the group of patients with good (The SNLG index < 2) and intermediate (2 < SNLG index < by 2.6) prognosis, the concentration of this cytokine was significantly lower than in those with poor prognosis (SNLG index > 2.6). There was a significant decrease of the total survival rates of NHL with serum IL-6 found. Therefore, IL-6 is a good prognostic marker in NHL and associated with the activity of a malignant process. Additionally, the increased serum IL-6 levels correlated with NK activities positively and with serum IL-4 levels negatively.     

Ridge regression: Application to nonexperimental data.

The value of regression analysis as a statistical tool may be significantly diminished when the set of independent or predictor variables are approximately collinear. The presence of approximate linear relationships in a set of predictors is not unusual for data that arise in social science research. This situation, often referred to as multicollinearity, may be difficult to detect and is even more difficult to remedy. A method called ridge regression has recently been developed and may be useful for solving some of the problems associated with multicollinearity. The ridge estimators have smaller variances (in comparison with those of ordinary regression), but they are biased. When the reduction in variance exceeds the square of the bias, ridge estimates are preferred. In this article, the ridge method is described. Its application is demonstrated by analyzing data from an employee satisfaction survey, (30 departmental units, each with 35 employees and a supervisor), and the ridge solution is compared with the regular regression solution. (27 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Multiple regression analysis of Jominy hardenability data for boron treated steels

The relations between chemical composition and their hardenability of boron treated steels have been investigated using a multiple regression analysis method. A linear model of regression was chosen. The free boron content that is effective for the hardenability was calculated using a model proposed by Jansson. The regression analysis for 1261 steel heats provided equations that were statistically significant at the 95% level. All heats met the specification according to the nordic countries producers Classification. The Variation in chemical composition explained typically 80 to 90% of the Variation in the hardenability. In the regression analysis elements which did not significantly contribute to the calculated hardness according to the F test were eliminated. Carbon, silicon, manganese, phosphorus and chromium were of importance at all Jominy distances, nickel, vanadium, boron and nitrogen at distances above 6 mm. After the regression analysis it was demonstrated that very few outliers were present in the data set, i.e. data points outside four times the standard deviation. The model has successfully been used in industrial practice replacing some of the necessary Jominy tests.     

Interrupted time-series analysis with brief single-subject data.

Assessing change with short time-series data is difficult because visual inference is unreliable with such data, and current statistical procedures cannot control Type 1 error because they underestimate positive autocorrelation. This article describes these problems and shows how they can be solved with a new interrupted time-series analysis procedure (ITSACORR) that uses a more accurate estimate of autocorrelation. Monte Carlo analyses show that, with short series, ITSACORR provides better control of Type 1 error than all previous procedures and has acceptable power. Clinical examples also show that ITSACORR is easy to use and functions well with real data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Comment on "Application of canonical correlational analysis to learning data."

B. N. Mukherjee (see 40:9) applied canonical correlation analysis to learning data published in other studies. On this basis, Mukherjee criticized J. F. Parker and E. A. Fleishman (see 36:2) for having arrived at a number of incorrect conclusions arising from their use of multiple rather than canonical correlations. However, Mukherjee's criticism was based on technical errors he introduced. This criticism was misdirected for Mukherjee's advocacy of canonical analysis was based on utility rather than necessity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Genetic analysis with hierarchical models

Apoptosis is a genetically programmed series of events that results in cell death. As a consequence, it is difficult to identify dominant genes that play a role in this process using genetic selections in conventional cell culture systems. Accordingly, we have established an efficient expression screen to isolate dominant, apoptosis-inducing genes. The assay is based on the apoptotic morphology induced in the human kidney cell line 293 after transient transfection of small plasmid pools from normalized cDNA expression libraries. Using this assay, we isolated a novel isoform of the proto-oncogene Neu differentiation factor (NDF), a ligand for erbB receptor tyrosine kinases. Several lines of experimental evidence indicate that this gene kills in a cell-autonomous fashion and independently of known erbB receptors. This apoptotic property of an NDF isoform is readily contrasted with NDF's transforming potential and might balance the tendency to tumorigenesis in cells that overexpress NDF.     

Measuring hospital cost efficiency with panel data models

Dopamine afferents from the mesencephalon appear to play a critical role in the normal development and cognitive functions of multiple areas of the primate cerebral cortex. In some regions, such as the prefrontal and motor cortices, dopamine innervation changes substantially during postnatal development. However, little is known about the postnatal maturation of dopamine afferents to the primate rostral entorhinal cortex, a periallocortical region that receives a dense dopamine innervation in adults. In this study, we used immunocytochemical techniques and antibodies against tyrosine hydroxylase and the dopamine transporter to examine the postnatal development of dopamine axons in the rostral subdivision of macaque monkey entorhinal cortex. Within animals, the axons labeled with each antibody did not differ in overall density or laminar distribution. Across development, the density of dopamine axons in layers I and VI did not change appreciably. In contrast, the density of labeled axons in layer III significantly increased by a factor of three between birth and 5-7 months of age. The timing of this change differs substantially from that observed in prefrontal cortex, where peak dopamine innervation occurs between 2 and 3 years of age. These findings, in concert with other data, suggest that developmental changes in the dopamine innervation of cortical regions may parallel the functional maturation of those areas.     

Integrative data analysis: The simultaneous analysis of multiple data sets.

There are both quantitative and methodological techniques that foster the development and maintenance of a cumulative knowledge base within the psychological sciences. Most noteworthy of these techniques is meta-analysis, which allows for the synthesis of summary statistics drawn from multiple studies when the original data are not available. However, when the original data can be obtained from multiple studies, many advantages stem from the statistical analysis of the pooled data. The authors define integrative data analysis (IDA) as the analysis of multiple data sets that have been pooled into one. Although variants of IDA have been incorporated into other scientific disciplines, the use of these techniques is much less evident in psychology. In this article the authors present an overview of IDA as it may be applied within the psychological sciences, discuss the relative advantages and disadvantages of IDA, describe analytic strategies for analyzing pooled individual data, and offer recommendations for the use of IDA in practice. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

p53 status has no prognostic significance in glioblastomas treated with radiotherapy

Mutation of the tumor suppressor gene TP53 and accumulation of the p53 protein are common events in the range of cerebral astrocytic tumors, including glioblastomas, but it is uncertain whether these events are associated with prognosis. Evidence suggests that the response of various tumors to radiotherapy may be influenced by the status of p53 which is involved in control of the cell cycle and apoptosis. This study tests the hypothesis that p53 governs survival in patients (n = 62) with glioblastomas who have received radiotherapy. Analysis of TP53 and p53 immunohistochemistry were undertaken using standard methods. TP53 mutations were present in 27% tumors, while 50% were p53-immunopositive (LI > 3%). A strong correlation (p < 0.0001) was found between a high p53 LI (> 50%) and the presence of a mutation, but p53 status at the level of gene or protein was unrelated to survival. Radiation-induced apoptosis that is independent of p53, and the presence in glioblastomas of genetic abnormalities that are also involved in the cellular response to radiation, such as deletions and mutations of pRb, are possible explanations of this result.     

Long-term survival data and prognostic factors of a complete response to chemotherapy in patients with head and neck cancer treated with platinum-based induction chemotherapy: a Hellenic Co-operative oncology Group study

Sudden infant death syndrome (SIDS) is the most common cause of postneonatal infant death in developed countries. The causes of SIDS remain unknown. The principal hypothesis appears abnormality of cardiorespiratory control, sleep-wake regulation. Also in our personal date the autopsy have not been of sufficient specificity and sensitivity to explain the disease.     

The analysis of profile data.

"Methods were suggested for handling 3 problems in the analysis of test profiles: measuring the similarity of profiles, discriminating the typical profiles of two or more groups, and clustering profiles into homogeneous groups. The suggested methods were, respectively, picturing profiles as interpoint distances in Euclidean space, use of the linear multiple-discriminant function, and factor analysis of profile cross-product terms. Some suggestions were given about transformations of profile data before further analysis." (PsycINFO Database Record (c) 2010 APA, all rights reserved)