codesup
maven repository: net. codesup. utilities » base - n - codec » 1. 0. 0
maven repository: net. codesup. util » jaxb - expression - plugin » 1. 1. 0
maven repository: net. codesup. util » jaxb - delegate - plugin » 1. 1. 0
maven repository: net. codesup. util » jaxb2 - rich - contract - plugin » 1. 6. 5
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you' re on a datepicker field. the down arrow will move you into the calendar table, where you can use the arrow keys to select the date, and use enter to make your selection. press escape to leave the datepicker. if you want to enter the date manually, the preferred format is: day (in two digits) - month (in three - letter abbreviation) - year (in four digits). be sure your arrival date is within the next year .
you' re on a datepicker field. the down arrow will move you into the calendar table, where you can use the arrow keys to select the date, and use enter to make your selection. press escape to leave the datepicker. if you want to enter the date manually, the preferred format is: day (in two digits) - month (in three - letter abbreviation) - year (in four digits). be sure your departure date is within four months of your arrival .
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provides a number of plugins for the jaxb (java api for xml binding) xml - schema - to - java compiler (xjc), that enhance the generated source code with various and configurable aspects, like
fluent builder
patterns, generating interface contracts from group and attributegroup declarations, generating javabeans (tm) bound and constrained properties, copy methods and - constructors, selective object graph copying, meta data generation etc .
small utility library to encode binary data to a representation with arbitrary radix. any given alphabet can be used as a grammar for the encoding .
jaxb plugin to generate arbitrary methods into xjc - generated classes that evaluate expressions in any programming language on the instance of the generated target class .
jaxb xjc plugin to generate real business logic methods inside generated classes. the implementation of the methods is done by generating delegation code to a corresponding utility class or an instance delegate .
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kara joyner, h. elizabeth peters, kathryn hynes, asia sikora, jamie rubenstein, and michael s. rendall
because of the importance of research on fathers in today’s policy debates, in the mid 1990s, the federal interagency forum on child and family statistics established working groups to develop recommendations for improving data and research on male fertility and fathering (federal interagency forum on child and family statistics 1998). this task force emphasized the need to include men in cycle 6 of the national survey of family growth (nsfg) and informed the collection of information on fathers in several recent surveys, including the 2002 nsfg and the 1997 cohort of the national longitudinal survey of youth (nlsy97). these data sets are widely used today to study topics such as men’s transition to fatherhood (e. g. , hynes et al. 2008) and multi - partner fertility (e. g. , guzzo and furstenberg 2007; manlove et al. 2008) .
the national maternal and infant health survey (nmihs) asked a large representative sample of women with live births during the year of 1988 to report the age of the father of their child, allowing researchers to estimate the number of births to men of different ages during that calendar year. lindberg and colleagues (1998) combined nmihs information on fathers’ ages with data from the u. s. census bureau to estimate nonmarital fertility rates for teen men in the population. they used the nmihs estimates to externally evaluate young men’s fertility reports from the 1988 and 1991 waves of the national survey of adolescent males (nsam). for the calendar year of 1988, they estimated a birth rate of 16. 4 per 1000 unmarried teen men based on the nmihs and 14. 1 based on young men’s self - reports in the nsam. the ratio of these rates indicates that as many as 87. 8% of unmarried teen births were reported by men in the nsam .
the more complete reports found in nsam could reflect the fact that the interval between the birth and the interview in which fertility histories were first collected was considerably shorter than in other surveys. nsam’s more complete reports could also reflect its innovative approach to collecting information about fertility. respondents were first asked to recall various sexual partners and then asked whether they had children with each partner. collecting fertility data within the context of relationship histories is intended to improve recall and appears to have been effective (lindberg et al. 1998) .
while both nsam and the nsfg collected information about births within the contexts of relationships, nsam obtained more complete reporting of births to teen men than did the nsfg. however, the assessments of male fertility data in these two surveys differ in some important respects. for instance, lindberg and colleagues (1998) relied on two waves of data to construct teen fertility rates .
by using parallel measures of male fertility across different surveys, a single method for estimating male fertility in the population, and analogous subgroups, we can make explicit comparisons of the quality of data across surveys. these comparisons allow us to identify aspects of surveys that improve the quality of male fertility data. furthermore, these comparisons offer us indicators of data quality in the nlsy79 and nlsy97, data sets that are widely used but have not been evaluated against an external standard .
even a survey with adequate representation of men and closely - spaced interviews would have incomplete reporting of men’s births if some men do not know about the birth of their children. the fragile families and child wellbeing study offers clues about men’s awareness of their paternity. for example, fragile families asked unmarried mothers about their relationship with the father at the time of the birth. only 1% of women could not identify the father of the birth, and another 9% had little or no contact with the father; the remainder of women reported they were in a friendship, marriage, or cohabiting relationship at the time of the birth (carlson, mclanahan, england, and devaney 2005). if we take an extreme position and assume mothers with little or no contact with the biological father at the time of the birth did not ever tell the father about the pregnancy, these results suggest that, at most, 10% of biological fathers may not be aware that they have a child. it is likely that some of these mothers did tell the fathers about the pregnancy, bringing the true share below 10% .
in order to evaluate the quality of male fertility data, we compare age - specific fertility rates (asfrs) in surveys to population rates based on data from the vital statistics and the u. s. census bureau. these rates are calculated similarly to those for women in the population (e. g. , hinde 1998; morgan, botev, chen, and huang 1999; preston et al. 2001). we calculate the fertility rate at age x (f x) for men as follows :
where b x is the number of births to men age x, and p x is the number of men age x in the population. we calculate asfrs that correspond to either periods or birth cohorts, depending on the focal survey, as we explain later. we estimate rates for all men and for different subgroups defined by race and marital status. we use birth certificate and population data that extend from 1972 to 2006 in order to cover the years that respondents in the surveys were at risk of having a birth .
while the calculation of asfrs is relatively straightforward, generating reliable estimates of b x and p x from the survey data and from the population data requires some assumptions. we first describe our methods for calculating the asfrs from these data sources. we then discuss our assumptions and potential biases they may introduce .
we use multivariate imputation by chained equations (allison 2001) to impute missing fathers’ ages for each calendar year of risk based on other information on the birth certificate: age of the mother, race of the mother, education of the mother, and race of the father. typically, mothers who fail to report the age of fathers also fail to report their race. to impute the number of births to men of different racial groups, we assume that the race of the father, when missing, is the same as that of the mother. 2
following the national center for health statistics’ procedures used for women, we compute marital - specific estimates of the number of men in the population by applying marital rates from the current population survey (cps) to our census estimates (nchs 2004; king et al. 2009). for instance, to estimate the number of married black men aged 18 in 2002, we multiply the proportion that is married (using three - year moving averages from the cps) by the number of men in this group (from the census data). 3
calculating fertility rates for the surveys similarly requires the number of births in the numerator and the number of men or women at risk in the denominator. for each survey, we create files of person - years lived by respondents to calculate fertility rates at each age from 15 to 24. the denominator includes the weighted number of respondents who contribute observations to a given age, and the numerator includes the weighted number of births to these respondents. in some analyses, we stratify age - specific fertility rates by race and marital status, using measures comparable to those used for the population. for instance, we estimate a nonmarital birth rate at the age of 18 by including the weighted number of single births to men at this age as the numerator and the weighted number of men who are single in the middle of this age interval in the denominator .
we use data from the nlsy79, the nlsy97, and the 2002 nsfg. all three data sets include substantial minority over - samples that facilitate the estimation of race - specific fertility rates; sampling weights for all three surveys adjust statistics so that samples are representative of their sampling frames .
the nlsy79 is a longitudinal survey that began with a representative sample of 14 to 21 - year - old men and women in 1979. respondents were interviewed annually until 1996 and biennially since that time. our analysis is based on data from the 1979–1995 interviews, allowing us to create person - years files for all respondents that extend through age 25. although the initial sample represents the civilian, noninstitutionalized population, the nlsy79 follows respondents if they become incarcerated or join the military, whenever possible .
both men and women in the nlsy79 were asked questions about their fertility behavior in each of the interviews. at the first interview, respondents were asked, “how many children, altogether, have (you ever given birth to / you ever had) at any time, not counting babies that were dead at birth? ” respondents who reported having any children were asked the dates of birth for each child. in subsequent rounds, the surveys alternated between updating from the previous survey (1980–1981; 1983–1994) and having respondents re - list any children they had ever had (1982; 1983 if missed the 1982 interview). the nlsy79 provides constructed fertility variables that incorporate several years of cleaning and editing (center for human resource research 2006) .
the nlsy79 also includes detailed information about each respondent’s marital history, including start and end dates of marriages and a measure of current marital status at each interview. the marital context of each birth is identified indirectly by examining respondents’ marital status in the month the child was born .
cycle 6 of the nsfg is, in contrast, a cross - sectional sample of women and men aged 15 to 45 in 2002 (lepkowski, mosher, and davis 2006). this cycle of the nsfg was the first to include men, but collected information on fertility using different instruments for men and women. cycle 6 collects information on male fertility with reference to specific sexual partners in hopes of eliciting higher reports of nonmarital fertility. men who report births are asked a direct question about whether he and the partner were married, cohabiting, or single at the time of each birth. in contrast, for nsfg women, fertility, marriage, and cohabitation histories are collected separately, and the relationship context of the birth is determined by comparing dates, as we do in the nlsy data .
in estimating both the birth and population counts, we make several assumptions. to the extent that these assumptions lead us to misestimate the number of births or number of individuals at risk of a birth, they create bias in the fertility rates. to the extent that we overestimate fertility rates in the population, surveys will appear worse than they actually are, whereas to the degree that we underestimate the population fertility rates, surveys will appear more favorable .
in estimating the number of men in the population, we assume that men who are in the armed forces overseas are at risk of having a birth in the united states. in results not presented here, we compared population asfrs for black and white men estimated with and without overseas armed forces men in two different calendar years (1991 and 2000). at any given age, the largest difference between these two sets of estimates was 0. 005. presumably, the bias posed by including the overseas armed forces men is likely to be small because such a small percentage of young men fall into this category .
displays the asfrs for three broad samples. results for women appear on the left, and results for men are displayed on the right. for all six groups, we display at each age the survey fertility rate, the population rate (indicated by vs for vital statistics), the difference between the rates, and the ratio of the rates (i. e. , the proportion of births reported). below the asfrs, we also present statistics that are averaged across five - year and ten - year age intervals. we weight each age equally in computing the averages for different age intervals, thus producing age - standardized ratios. for each ratio, we indicate whether the survey rate is significantly different from the population rate .
notes: fertility rates for different age groups are computed by averaging the asfrs comprising them (weighting each age equally) .
all three surveys obtain almost complete reporting of women’s fertility: the 10 - year age ratios range from 0. 973 to 0. 986. the ratios for men are considerably lower and exhibit greater variability. the 10 - year age ratio for nsfg is 0. 805, while the ratios for nlsy79 and nlsy97 are 0. 885 and 0. 888 respectively. the ranking of these overall ratios for men is consistent with our hypothesis about the importance of longitudinal data, with the nlsys capturing a greater share of male births than the nsfg. the nlsy97 does not appear to be substantially better than the nlsy79 at capturing early male fertility, but these first analyses do not distinguish marital and nonmarital births. for these broad age intervals, the only survey rate that differs significantly from the population rate is for the nsfg men .
comparing the ratios averaged across ages 15–19 for the different surveys again suggests that the nlsy surveys do a better job of capturing births than the nsfg. the value for nsfg men indicates that this survey misses almost one - third of births to teen men. differences for the group aged 20 to 24 are less pronounced, but reveal a similar pattern .
to facilitate interpretation, we present the remaining comparisons of survey and population asfrs in graphs. in
, we compare vital statistics’ rates (using multiple imputation for missing father’s age) to estimates of male fertility based on the nsfg women’s reports of the fathers’ ages of their children born in this period (1991 to 2000). the nsfg rates include the weighted number of births to men of different ages (based on the nsfg female data) in the numerator and the weighted population of nsfg men at different ages (based on the nsfg male data) in the denominator. it is reassuring to note that the rates based on the nsfg women’s reports map closely to the population estimates. this suggests that our population - based rates are fairly accurate, and that any differences we see in the nsfg male asfrs are due to differences in the reporting of births (the numerator) rather than the representation of men in the survey (the denominator) .
age - specific fertility rates for men by data source: 1991 to 2000 period (ratio of rates r =. 805 * )
note: hollow circle means survey estimate different from population at p <. 05 (two - tailed test) .
we now turn to analyses that pertain to specific subgroups of men, beginning with the nsfg .
displays six separate graphs for nsfg men in the 1990s. the first graph (a) copies survey and population estimates from
. the second graph (b) drops foreign - born men who were not yet in the u. s. at a given age of risk to better capture men who were actually at risk of having a birth in the period. in this graph, and other analyses based on the nsfg (not shown), we find that excluding this group does not make a substantive difference. in the remaining graphs, we include the foreign born because studies based on fatherhood in the nsfg typically include this group (e. g. ,
). the following graphs compare the asfrs for four specific groups: white men (c), black men (d), single men (e), and married men (f). we do not take into account race and marital status simultaneously in our nsfg analyses because of small sample sizes for some subgroups, particularly black married men. results indicate that for white men, there is some underreporting of births (
=. 824). for black men, the gap between the population and survey estimates is much larger, and the gap increases with age. as expected, births to single men are underreported. in contrast, none of the survey estimates for married men differ significantly from the population estimates .
notes: line corresponds to rate estimated for the population using mice; significant differences between the survey and population rate at any given age are indicated by the hollow circles .
): some differences are significant, but they are small in magnitude. as in the nsfg, births to black men are significantly underreported; however, in the nlsy79, the magnitude of underreporting is smaller, and it is statistically significant only in the early 20s. the results for single men resemble those for all men, with significant but small birth deficits among the three oldest ages. as expected, the asfrs for married men from the nlsy79 do not significantly differ from those for the population, with the exception of the rate at age 18 .
displays these graphs for men from the nlsy97. as in the case of the nsfg, the patterns for whites and single men from the nlsy97 closely resemble the overall patterns of men in this sample, with small deficits between the ages of 21 and 24. it is reassuring to observe once again that the asfrs for men in the nlsy97 are close to those estimated for the population. in contrast to the other surveys, the nlsy97 does not show significant differences between the population estimates and the survey estimates for black men .
in other analyses (results not shown) for blacks and whites from the nlsy79 and nlsy97, we excluded those who had ever been in military barracks. we alternatively ran analyses that excluded respondents who were in prison or on military barracks during a given age of year of risk. none of these exclusions changed the overall pattern of results for white and black men. this partly reflects the fact that respondents in these institutions comprised a small proportion of the entire sample .
our imputation methods assume that fathers with missing information on race (who typically have missing information on age as well) are the same race as mothers. we conducted sensitivity tests for men in the population from the 1980–84 birth cohort (the group most likely to violate this assumption because of increases in interracial relationships) to obtain an idea of how much distortion our homogamy assumption may create in the race - specific population asfrs (results not shown). first, we assumed that the racial mix of parents at each age was the same for births with and without information on birth certificates. based on this assumption, we ended up reducing the number of births to white men at every age and increasing the number to black men, but the asfrs for black and white men barely changed. then, we repeated this exercise, assuming racial mixing was more common for births certificates with missing race. this alternative assumption did not dramatically change the patterns in these graphs .
because marital status differs considerably by race, the confounding of race and marital status in these graphs makes it difficult to identify whether black men or single men are responsible for the observed underreporting of births .
presents nonmarital asfrs for nlsy79 and nlsy97 by race. for men from the nlsy79, we present two sets of these graphs: one set is based on the mott and colleagues’ data removing births with low confidence births paternity codes (a and c) and the other based on the set of constructed variables without the mott and colleagues’ changes (b and d). as can be seen, the pattern of results does not differ according to which set we use; however, there is an increase in underreporting for white men with the mott and colleague’s changes (i. e. ,
researchers have been concerned that incomplete reporting of men’s births in surveys will bias the coefficients in multivariate models of the antecedents and consequences of early fertility. previous studies that have estimated parallel models of early parenthood find weaker effects of many family background variables for men compared to women (e. g. , hynes et al. 2008; michael and tuma 1985), but it is unclear whether these sex differences are due to differences in data quality or behavior .
). we use a sample of women for these simulations because we want to have initial models that are not biased by under - reporting or representation issues. we use the nsfg for these simulations. we limit the sample to women aged 20 or older at the time of the interview and estimate a logistic regression model predicting the likelihood of having a teen birth as a function of basic family background and demographic variables. we discard information on the exact timing of teen births in order to simplify our experiments. odds ratios for this model appear in column one of
notes: we examine whether the 95% confidence interval corresponding to the estimate for each simulated includes the estimate from the model based on complete birth reports. confidence intervals do not include the point estimate are classified signficantly different .
in our second experiment, we once again change 30% of the teen births to the no birth category; however, we assume greater underreporting among blacks than among other respondents based on their respective proportions of teen births underreported for our nsfg sample (43% of teen births to black men and 23% for non - black men). all other steps remain the same. for each variable in the two experiments that we conduct, we present the average of the 100 coefficients in columns 2 and 5. in addition, we report the percent difference between the averaged coefficients and the original estimates (columns 3 and 6) and the percent of the 100 models with coefficients that are significantly different from the original estimates (columns 4 and 7) .
the results for the first experiment reveal a decline in magnitude of coefficients for each of the family background variables, with an average decline of around 10% . still, the vast majority of coefficients from the first experiment fail to significantly differ from the original estimates. in the second experiment, the coefficient for “black” declines by almost 50% and is significantly different from the original estimate in all of the simulated samples; this is consistent with the assumption of differential underreporting in this simulation. the attenuation of the other coefficients is generally weaker than in the first experiment. the results of these experiments suggest that underreporting attenuates coefficients in models of having a teen birth, especially the coefficients of variables associated with underreporting .
researchers are increasingly emphasizing the importance of men in studies of family formation (bachrach 2007; forste 2002; goldscheider and kaufman 1996; greene and biddlecom 2000). at the same time, they continue to express concerns about the quality of male fertility data in recent surveys. in response to these concerns, we estimated age - specific fertility rates during the teens and early twenties for men in nlsy79, nlsy97, and nsfg 2002 and compared them to male fertility rates estimated for the u. s. population. we found that in the nsfg, roughly four out of five early births were reported, and in the nlsy79 and nlsy97, almost nine - tenths of early births were reported. in all three surveys, reporting deficits were especially pronounced for nonmarital births. reporting of births to women was virtually complete in all three surveys .
in spite of the fact that nonresponse rates were considerably higher in the nlsy97 than in the nlsy79 (aughinbaugh and gardecki 2008), we found a slightly greater proportion of nonmarital births reported for this more recent cohort (i. e. ,. 858 versus. 829). several factors could have improved reporting of nonmarital births, including the development of the fatherhood movement, greater paternity establishment, and increases in the proportion of nonmarital births that were to cohabiting parents (kennedy and bumpass 2008; marsiglio, amato, day, and lamb 2000) .
results from our monte carlo experiments, which are based on levels of underreporting found for men in the nsfg, suggest that underreporting attenuates coefficients in models of early fatherhood. furthermore, the magnitude of attenuation depends on how strongly a given variable is associated with underreporting; however, the attenuation of coefficients in models of teen births estimated for men from the nlsy79 and nlsy97 is likely to be smaller because a larger proportion of births in these surveys are reported .
while we were not able to conduct separate analyses of hispanics due to limitations in the population data, we would be concerned about the reliability of these estimates nonetheless. the composition of the hispanic population changes across cohorts and even within cohorts at different ages due to immigration (portes and rumbaut 1996). the further we follow nlsy hispanics beyond the first interview, the less they will resemble hispanics from the same birth cohorts in the general population .
this study makes an important contribution to our understanding of the quality of male fertility data in major u. s. surveys. in the period following the nurturing fatherhood initiative, research on men’s fertility has proliferated. yet, our understanding of the quality of male fertility data is based on studies that are now dated. our results reveal that the quality of male fertility data in the nlsy97 and the nlsy79 is better than that in the nsfg, suggesting that survey design matters to the quality of these data. they suggest that surveys collecting information on fertility for men prospectively are likely to be more successful than studies that collect this information retrospectively .
1 information on marital status in the vital statistics data has varied across states and over time. the majority of states ask directly whether the mother was married “ at birth, conception, or any time in between, ” or alternatively, whether she was married to the father of the child. a few states determine marital status using inferential procedures (see hamilton, martin and ventura 2006 and ventura and bachrach 2000 for greater detail on how marital status is measured in the vital statistics. )
2 we also used the hotdeck method to impute missing fathers’ ages. first, we stratified the birth certificate data by calendar year, mother’s age, and father’s race. then, for each stratum (e. g. , births to black fathers and 18 - year - old mothers in 1980), we randomly selected (with replacement) ages of fathers reported on birth certificates to fill in the father’s age when it is missing. this alternative method of imputation produced estimates of the number of births to men that are remarkably close to those based on multivariate imputation .
3 to develop comparable measures of race for data from years 2000 and beyond, we bridged the responses of those who reported more than one race to a single race using the largest group bridging method (nchs 2004) .
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input arrangements for transferring data to be processed into a form capable of being handled by the computer; output arrangements for transferring data from processing unit to output unit, e. g. interface arrangements
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image processing system filed june 50, 1965 2 sheets - sheet l 11 ckt 29 - d / a d / a co - v conv i 2 x3 3 2 y - b x2 34
3 2 1 1 character end wa conv b r point gen i defl 21 register 3, 25 comp reg decoder inventor william h. ass
6 i' m m attorney dec. 30, 1969 william h. sass 3, 487, 202
image processing system filed june 30. 1965 v 2 sheets - sheet 2 m endpoints (x' y') de designation pattern mgscnou i 2 4 5 6 0 000 m 1 0, 2 0, 5 2, 7 5, 7 7, 5 7, 2 1 00 | 0, 5. 2, 7 5, 7 7, 5 7, 2 5, 0 2 0 | 0 2, 7 5, 7 7, 5 7, 2 5, 0 2, 0 5 on j 5, 7 7, 5 7, 2 5, 0 2, 0 0, 2 4 100 u 7, 5 7, 2 5, 0 2, 0 0, 2 0, 5 5 | 0 | l 7, 2 5, 0 2, 0 0, 2 0, 5 2, 7
united states patent ofiice 3, 487, 202. patented dec. 30, 1969 3, 487, 202 image processing system william h. sass, ulster park, n. y. , assignor to international business machines corporation, armonk, n. y. , a corporation of new york filed june 30, 1965, ser. no. 468, 413 int. cl. g061: 9 / 00 us. cl. 235 - 616 4 claims abstract of the disclosure this invention relates to image processing and more specifically to a line or edge follower for tracing or following a line or object whereby the image may be reduced to digital data .
it has become increasingly apparent that digital computers, especially those of the general purpose variety, may be useful in solving a variety of graphic design problems which range from the actual design to the storage and reproduction of graphic information. one of the essential features of any such system is the ability to examine an image and translate the information con tained therein into a format compatible with the computer system, such that the information may be assimilated into the computer, altered if desired, and reproduced either in its original or altered form at a later time .
the image may be examined in a number of different ways. however, of these the flying spot scanner has been the most successful. in this type system the image may be reduced to a transparency and illuminated by the moving beam of a cathode ray tube while a photo multiplier tube examines the light transmission through the film. since the position of the beam or flying spot is known at all times the output of the photo multiplier tube, in time sequence, indicates the transparency of the areas illuminated by the beam in the course of its movement over the image. the flying spot scanning device may also be implemented with an opaque image by detecting reflected light .
one object of the invention is to provide an image processing system in which the analog image data is directly converted in scanning to digital data for controlling the scanning operation and defining the image .
another object of the invention is to provide an image processing system which utilizes a selected portion of a polygon shaped tracking pattern for generating digital response indicative of image position .
a further object of the invention is to provide an image processing system which is compatible for use with digital processing equipment and which relieves the processor of many functions .
the invention contemplates an image processing system comprising means for generating in time sequence the successive end point coordinates defining one of a plurality of partial polygon patterns in response to a coded signal, means responsive to said end point signals for generating a plurality of time sequential scanning line segments for scanning an image, means for examining the image during scanning and generating a plurality of signals indicative of the transmissivity of the image during each line segment scan, and means responsive to the said signals for providing a digital signal indicative of the relative placement of the image with respect to the partial polygon pattern generated.
codesup is a private corporation in pudahuel , santiago , chile founded by local private companies of pudahuel in order to aim for sustainable development in particular in social , economic and environmental areas . 
codesup is a private corporation in pudahuel, santiago, chile founded by local private companies of pudahuel in order to aim for sustainable development in particular in social, economic and environmental areas.
codesup is a private corporation in pudahuel, santiago, chile founded by local private companies of pudahuel in order to aim for sustainable development in particular in social, economic and environmental areas.