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Results for “Birth Order--statistics”

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PubMed1979

Choice of ascertainment model II. Discrimination between multi-proband models by means of birth order data.

Probability models have been developed for family data, where each family has been selected or ascertained through a group of m probands, where m is a known parameter, not a random variable. The birth orders of the probands among the affected children are reported for each family. It is demonstrated that this information is sufficient for choice of ascertainment model. The conditional probability that an ascertained family with s children has r affected ones, depends, in addition to the segregation parameter, on the birth order of the youngest proband only. By means of the joint distribution of the birth orders of the other probands, it can be demonstrated if the ascertainment takes place through affected children near to or distant from each other in relative birth orders. Statistical methods have been developed for cases with two and cases with m probands.

Birth Order↗
PubMedDate not supplied

Delayed childbearing in Canada: trends and factors.

"Using period and cohort birth order statistics, an overview of the phenomenon of delayed childbearing in Canada is presented. Data employed in the period analysis were mainly from the years 1944 to 1985, while women born between the years 1935 and 1960 were the subjects of the cohort analysis. An examination of selected indices, namely, age-specific first-birth fertility rates, median ages of women at first-order birth and cumulative first-order birth rates shows that there is an overall trend for women to postpone the initiation of childbearing until late twenties or early thirties.... The results indicate that work experience, education, occupation and year of marriage are important variables influencing age at first birth and first-birth interval." (SUMMARY IN FRE AND ITA)

Age Factors↗
PubMed1999

[Study of ultrasonographic image textures with second-order statistical methods].

BACKGROUND: We report the sonographic image texture of the neonatal heart in different stages of development by calculating numerical parameters extracted from the gray scale cooccurrence matrix. To show pixel values differences and enhance texture structure, images were equalized, and then the gray level range was reduced to 16 to allow for sufficiently high occupancy frequency of the cooccurrence matrix. MATERIALS AND METHODS: We measured B-mode US images, all acquired with the same unit, using the same setup (gain, frequency, constant TGC). For each case measurements were made on 3 diastolic images by selecting a 32 x 64 pixel on the interventricular septum ROI. This procedure was applied to 3 different examinations made at birth, at 3 days, and after a month of life. For each 8 bit image we obtained a coocurrence matrix by sampling adjacent pixels at 0 degree, from which we calculated entropy; then the images were equalized and converted to 4 bit format; on these processed images we calculated 4 gray scale coocurrence matrix samplings adjacent pixels at angles of 0 degree, 45 degrees, 90 degrees, and 180 degrees. Parameters obtained from different angles cooccurrence matrix were averaged to get a numerical parameter independent of sampling angles. RESULTS: The one-way analysis of variance and Student's "t"-test were performed on the parameters obtained from 3 different examinations and the differences among different developmental stages are 95% significant. No significance was obtained comparing images at birth with those at 3 days. CONCLUSIONS: Differences are so little significant that they may be due to different factors affecting image texture and the variability introduced by manual ROI positioning; therefore no definitive conclusions can be drawn as to considering this kind of analysis capable of discriminating different stages of myocardial development. To apply this analysis to routine US examinations, different correction factors for range, azimuth, and focal dependence of texture must be considered.

Mathematics↗