Design and Statistical Analysis for the Myopia Intervention Trial in Taiwan

2000 ◽  
pp. 161-164 ◽  
Author(s):  
C. K. Hsiao ◽  
C. J. Chen ◽  
Y.-F. Shih ◽  
L. L.-K. Lin ◽  
Por T. Hung ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Intervention Trial

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

Rice Fortified with Iron Given Weekly Increases Hemoglobin Levels and Reduces Anemia in Infants: a Community Intervention Trial

2013 ◽  
Vol 83 (1) ◽  
pp. 59-66 ◽  
Author(s):  
Francisco Plácido Nogueira Arcanjo ◽  
Paulo Roberto Santos ◽  
Álvaro Jorge Madeiro Leite ◽  
Francisco Sulivan Bastos Mota ◽  
Sérgio Duarte Segall
Keyword(s):  
Community Intervention ◽  
Capillary Blood ◽  
Number Needed To Treat ◽  
Intervention Trial ◽  
Day Care Centers ◽  
Control Center ◽  
Ferric Pyrophosphate ◽  
Child Day Care ◽  
Child Day Care Centers ◽  
The Impact

More than two billion people suffer from anemia worldwide, and it is estimated that more than 50 % of cases are caused by iron deficiency. In this community intervention trial, we evaluated infants aged 10 to 23 months of age (n = 171) from two public child day-care centers. Intervention lasted 18 weeks. The 50-g individual portion (uncooked) of fortified rice provided 56.4 mg of elemental iron as ferric pyrophosphate. Capillary blood samples to test for anemia were taken at baseline and at endpoint. The objective of this study was to evaluate the impact of rice fortified with iron (Ultrarice®) on hemoglobin and anemia prevalence compared with standard household rice. For the fortified rice center, baseline mean hemoglobin was 113.7 ± 9.2 g/L, and at endpoint 119.5 ± 7.7 g/L, p < 0.0001; for the standard rice center, baseline mean hemoglobin value was 113.5 ± 40.7 g/L, and at endpoint 113.6 ± 21.0, p = 0.99. Anemia prevalence for the fortified rice center was 27.8 % (20/72) at baseline, and 11.1 % (8/72) at endpoint, p = 0.012; for the control center, 47.1 % (33/70) were anemic at baseline, and 37.1 % (26/70) at the end of the study, p = 0.23. The Number Needed to Treat (NNT) was 4. In this intervention, rice fortified with iron given weekly was effective in increasing hemoglobin levels and reducing anemia in infants.

Intraindividual Variability in Development Within and Between Individuals

2001 ◽  
Vol 6 (3) ◽  
pp. 187-193 ◽  
Author(s):  
John R. Nesselroade
Keyword(s):  
Statistical Analysis ◽  
Research Design ◽  
Intraindividual Variability ◽  
Factor Analytic

A focus on the study of development and other kinds of changes in the whole individual has been one of the hallmarks of research by Magnusson and his colleagues. A number of different approaches emphasize this individual focus in their respective ways. This presentation focuses on intraindividual variability stemming from Cattell's P-technique factor analytic proposals, making several refinements to make it more tractable from a research design standpoint and more appropriate from a statistical analysis perspective. The associated methods make it possible to study intraindividual variability both within and between individuals. An empirical example is used to illustrate the procedure.

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