Generalizing the Causal Effect of Fertility on Female Labor Supply

Abstract We study the effect of fertility on labor supply in Argentina and Mexico exploiting a source of exogenous variability in family size first introduced by Angrist and Evans (1998) for the United States. Our results constitute the first external validation of the estimates obtained for the US. External validation of empirical results is central to the making of rigorous science, but there are very few attempts to establish it. We find that the estimates for the US can be generalized both qualitatively and quantitatively to the populations of two developing countries where, compared to the US, fertility is known to be higher, female education levels are much lower and there are fewer facilities for childcare.Causality, Internal and External Validity, Childbearing and Female Labor Supply

Generalizing the Causal Effect of Fertility on Female Labor Supply

Abstract We study the effect of fertility on labor supply in Argentina and Mexico exploiting a source of exogenous variability in family size first introduced by Angrist and Evans (1998) for the United States. Our results constitute the first external validation of the estimates obtained for the US. External validation of empirical results is central to the making of rigorous science, but there are very few attempts to establish it. We find that the estimates for the US can be generalized both qualitatively and quantitatively to the populations of two developing countries where, compared to the US, fertility is known to be higher, female education levels are much lower and there are fewer facilities for childcare.http://deepblue.lib.umich.edu/bitstream/2027.42/40011/2/wp625.pd

Validation of a Predictive Model for Survival in Patients With Advanced Cancer: Secondary Analysis of RTOG 9714.

BackgroundThe objective of this study was to validate a simple predictive model for survival of patients with advanced cancer.MethodsPrevious studies with training and validation datasets developed a model predicting survival of patients referred for palliative radiotherapy using three readily available factors: primary cancer site, site of metastases and Karnofsky performance score (KPS). This predictive model was used in the current study, where each factor was assigned a value proportional to its prognostic weight and the sum of the weighted scores for each patient was survival prediction score (SPS). Patients were also classified according to their number of risk factors (NRF). Three risk groups were established. The Radiation Therapy and Oncology Group (RTOG) 9714 data was used to provide an additional external validation set comprised of patients treated among multiple institutions with appropriate statistical tests.ResultsThe RTOG external validation set comprised of 908 patients treated at 66 different radiation facilities from 1998 to 2002. The SPS method classified all patients into the low-risk group. Based on the NRF, two distinct risk groups with significantly different survival estimates were identified. The ability to predict survival was similar to that of the training and previous validation datasets for both the SPS and NRF methods.ConclusionsThe three variable NRF model is preferred because of its relative simplicity

What does validation of cases in electronic record databases mean? The potential contribution of free text

Electronic health records are increasingly used for research. The definition of cases or endpoints often relies on the use of coded diagnostic data, using a pre-selected group of codes. Validation of these cases, as ‘true’ cases of the disease, is crucial. There are, however, ambiguities in what is meant by validation in the context of electronic records. Validation usually implies comparison of a definition against a gold standard of diagnosis and the ability to identify false negatives (‘true’ cases which were not detected) as well as false positives (detected cases which did not have the condition). We argue that two separate concepts of validation are often conflated in existing studies. Firstly, whether the GP thought the patient was suffering from a particular condition (which we term confirmation or internal validation) and secondly, whether the patient really had the condition (external validation). Few studies have the ability to detect false negatives who have not received a diagnostic code. Natural language processing is likely to open up the use of free text within the electronic record which will facilitate both the validation of the coded diagnosis and searching for false negatives

Generalizing the Causal Effect of Fertility on Female Labor Supply

We study the effect of fertility on labor supply in Argentina and Mexico exploiting a source of exogenous variability in family size first introduced by Angrist and Evans (1998) for the United States. Our results constitute the first external validation of the estimates obtained for the US. External validation of empirical results is central to the making of rigorous science, but there are very few attempts to establish it. We find that the estimates for the US can be generalized both qualitatively and quantitatively to the populations of two developing countries where, compared to the US, fertility is known to be higher, female education levels are much lower and there are fewer facilities for childcare.Fertility, labor supply, causality, instrumental variables

Numeracy, literacy and ESOL: evaluation of entry and level 1 awards (National report from the Inspectorate 1998-99)

During the past 20 years a range of awards has been developed to meet the demand for external validation of students’ achievements. Since the introduction of the Further and Higher Education Act 1992 (the Act) there has been a particularly sharp increase in the use of external awards to accredit the achievements of students wanting to improve their literacy and numeracy, and those wishing to improve their spoken and written English. It is often mistakenly thought that external awards are necessary to meet the requirements of schedule 2 of the Act, to secure funding from the Further Education Funding Council (FEFC), and to meet the requirements of colleges’ own information systems. Most students now study for an award. This inspectorate national exercise was devised to evaluate those awards which are frequently used at entry level and level 1 in numeracy, literacy and English for speakers of other languages (ESOL) and to judge the impact of these qualifications on the curriculum, teaching and learning, and on students’ achievements

The use of near infrared reflectance spectroscopy (NIRS) for prediction of the nutritive value of barley for growing pigs

peer-reviewedThere is a need in the feed industry for a rapid means of evaluating the nutritive value of feeds and feed ingredients. Chemical analysis provides only basic information and most of the laboratory techniques take too long for this information to be of use in feed formulation at the feed mill. Near infrared reflectance spectroscopy (NIRS) has been proposed as an alternative means of predicting nutritive value. In this study, NIRS was used to predict the digestible energy (DE) concentration and in vitro ileal digestibility of crude protein (CP) and total-tract digestibility of energy of locally produced barley. The calibration and validation statistics were developed using modified partial least squares (MPLS). Derivatisation and scatter correction procedures were carried out to reduce interference from external effects. The correlations between actual and predicted DE values, based on both calibration (R2 0.93) and validation (R2 0.69), were strong with corresponding low standard errors of calibration (SEC) and cross validation (SECV) (SEC 0.128, SECV 0.279). Strong correlations were also observed between predicted and actual in vitro digestibility values for both calibration and validation exercises. It was noted that validation weakened the correlations (R2 0.73 vs. 0.50 for in vitro ileal digestibility of CP and 0.80 vs. 0.68 for in vitro total tract digestibility of energy) and fractionally increased the standard errors (0.016 vs. 0.020 for in vitro ileal digestibility of CP and 0.018 vs. 0.024 for in vitro total tract digestibility of energy). The correlations obtained by cross validation of the lowest SECV equations were not significantly different to those obtained by the scatter correction treatments. The strong relationships and low standard errors obtained between the actual and predicted values indicates that NIRS may be of use in predicting the nutritive value of barley for growing pigs, although more research is required to include larger sample sets