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Results for “Data Aggregation”

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At least 19 recordsLinked to original sources

PubMed1993

On the influence of data source in aggregated data studies: a comparative study of suicide information based on death certificates and judicial files.

STUDY OBJECTIVE: The aim was to assess the differences in suicide data obtained from different database sources. DESIGN: Death certificate based data on suicidal deaths were compared with the information obtained from the non-natural death investigation files at the Public Prosecutor's Office. SETTING: The study was confined to the time period of 1981-1984 and to the residents of the district of Leuven (Belgium) who died in the district. MAIN RESULTS: Differences were found in the number of suicidal deaths reported as well as in the demographic variables, the distribution of suicide methods, and the place of death. Sixty percent of the records in both databases could be matched for all variables studied (age, gender, civil state, place of death, and suicide method), and another 10% if only place of death was allowed to differ. For 4.5% of the cases in the judicial files and for 8% of the records in the official statistics database no corresponding record from the other data source could be found. Based on simple probability statistics [P(missing record)+P(different information[present)] the possible minimum global information bias could be estimated to range from 7 to 42%. CONCLUSIONS: Different epidemiological pictures of suicide mortality may result from studying different data sources.

Belgium↗

PubMedDate not supplied

Design considerations for estimation of exposure effects on disease risk, using aggregate data studies.

Previously we proposed an aggregate data study design for estimation of exposure effects from population-based disease rates and covariate data from risk factor surveys in each population group. A basic relative rate model specified for individuals is aggregated to produce a random effects relative rate model for the disease rates. Relative rate parameter estimates from aggregate data studies target the same parameters as individual-level studies but use between-group information in the data. We distinguish aggregate data studies from ecologic studies. Considerations in the design of aggregate studies are motivated by the need to gain clearer understanding of the role of diet in cancer aetiology. Simulation studies show that increasing the number of populations included in an aggregate data study from about 20 to 30-40 gives greater improvement in power than corresponding increases in the size of the survey sample in each population over an initial size of 100 individuals.

Aged↗

PubMed1989

The use of aggregate data in alcohol epidemiology.

Analyses of aggregate data have the potential of elucidating pivotal issues in alcohol epidemiology, in particular those singled out by the public health perspective, such as the impact of per capita alcohol consumption on various damage rates. This article discusses the possibilities and limitations of the two main approaches in the analysis of aggregate data, focusing upon ecological and time series data, respectively. In addition, a synthetic approach is outlined, which aims at an integration of macro and micro findings. In that context it is shown how effect measures which are normally based on micro data (relative risk and attributable fraction) can be derived from macro data.

Alcoholism↗

PubMed1997

Increasing correlations between personality traits and cortisol stress responses obtained by data aggregation.

Attempts to link personality traits and cortisol stress responses have often been inconclusive. The aim of this paper was to investigate this association by aggregating cortisol stress responses. Therefore, 20 healthy men were exposed to a task consisting of public speaking and mental arithmetics in front of an audience on five days. Six cortisol levels were measured in relation to the stressful task obtained at 10-min intervals on each day. Psychological assessment included the Questionnaire for Competence and Control (FKK) and the Giessen-Test (G-T). These questionnaires focus on assessing personality traits, i.e. locus of control and self-concept. Areas under the response curve (AUC) of the six cortisol samples were computed to obtain an index of the individual's cortisol stress response on each day. Since novelty is a random situational factor likely to mask individual differences in the stress response, the AUC cortisol stress responses of days two to five were consecutively aggregated, excluding the first day. Scales of the two questionnaires employed did not correlate with the AUC cortisol stress response of the first stress trial. The correlation pattern of the AUC cortisol measures of days two to five with the questionnaire scales was inconclusive. However, significant correlations emerged with an increasing number of cortisol stress responses aggregated. Correlations between the measure of social dominance and aggregated AUC cortisol stress responses rose from r = -.47 on day two of the experimental session to r = -.70 after aggregating days two to five. Similarly, measures of locus of control and cortisol stress responses became increasingly correlated with aggregation of several stress exposures. These data provide preliminary evidence for a relationship between questionnaire scales aiming at assessing personality traits and cortisol stress responses uncovered by repeated stress exposure and data aggregation. While novelty may mask the impact of personality on the cortisol stress response on the first exposure, differences in the ability to cope with the stressful situation may lead to different cortisol stress response patterns on subsequent stress exposures. With data aggregation, an association between the trait component of cortisol stress responses and questionnaire scales might be uncovered. For reliable investigation of correlations between personality variables and cortisol stress responses, repeated stress exposure and data aggregation is suggested.

Adult↗

PubMed2006

Lay people's perception of food hazards: comparing aggregated data and individual data.

The psychometric paradigm has been used to explain the perception of food hazard risks. In past studies, only aggregated data were analyzed, and individual differences were neglected. In the present study, both aggregated data and non-aggregated data are analyzed. Data stem from a mail survey conducted in Switzerland (N=448). Analyzing aggregated data, results of past studies were successfully replicated. The PCA analysis revealed the two factors "unknown risk" and "dread risk." Results of a three-way component analysis (3MPCA) suggest, that two components explain individual differences in the perception of food hazards. The two components were labeled "unobservable hazards," and "familiar hazards." Individual differences in the cognitive representation of hazards were correlated with attitudes toward natural foods. Results suggest that people who prefer natural foods differ in perceived risks from people who do not prefer natural foods. Results show that methods permitting individual differences are crucial for a better understanding of the cognitive representation of food hazards.

Adult↗

PubMed2002

[Data aggregation in measuring inequalities and inequities in the health of populations].

OBJECTIVES: To compare how different degrees of data aggregation influence the measurement of health inequalities and health inequities within a population, and to assess the appropriateness of those different degrees of data aggregation in performing studies on inequalities and inequities. METHODS: As an example, we used data on the infant mortality rate in Costa Rica in 1973 and in 1984 and calculated measurements that are frequently used to quantify inequalities and inequities. RESULTS: According to our results, the inequality measures presented (except for those that were derived using regression models) are not sensitive to data aggregation by socioeconomic groups. However, when geographic areas are compared, more disaggregation of the data results in the measures indicating greater inequality. CONCLUSIONS: Our results show that some measures can vary widely depending on the level of data aggregation. It is thus crucial to know how to select these measures and also how to aggregate the data in a way that is consistent with the objectives of each study.

Costa Rica↗

PubMed2002

A hierarchical aggregate data model with spatially correlated disease rates.

The aggregate data study design (Prentice and Sheppard, 1995, Biometrika 82, 113-125) estimates individual-level exposure effects by regressing population-based disease rates on covariate data from survey samples in each population group. In this work, we further develop the aggregate data model to allow for residual spatial correlation among disease rates across populations. Geographical variation that is not explained by model predictors and has a spatial component often arises in studies of rare chronic diseases, such as breast cancer. We combine the aggregate and Bayesian disease-mapping models to provide an intuitive approach to the modeling of spatial effects while drawing correct inference regarding the exposure effect. Based on the results of simulation studies, we suggest guidelines for use of the proposed model.

Bayes Theorem↗

PubMed2002

The use of aggregate data for measuring practice improvement.

Practice improvements are much needed in health care but are difficult to implement and to measure. Without records that include aggregate data, outcomes cannot be compared. Aggregate data are defined as data not limited to one patient, but data that are tracked across time, across organizations, across patient populations, or across some other variable. There are several issues that complicate the gathering of aggregate data, including data availability, format, management and definition, as well as the processes of trending and comparison to a standard benchmark.

Benchmarking↗

PubMed2005

Survival analysis on aggregate data to assess time to sero-conversion after experimental infection with Bovine Leukemia virus.

Bovine Leukemia virus (BLV) is a ubiquitous retrovirus that affects mainly cattle. Knowledge of the precise moment of infection is fundamental for identification and evaluation of factors related to BLV transmission. Systematic reviews and meta-analyses provide good evidence on the effects of medical interventions. The objectives were to estimate time to sero-conversion after experimental infection using data from retrieved literature and to detect factors that may influence the length of that interval using survival analysis on pooled data. An analysis using aggregate data from 36 studies totalling 438 observations was performed. From this, four sets were created and analysed by interval-censored accelerated failure time models (AFT) with different distributions (exponential, Weibull, log-logistic, lognormal and generalized gamma), and some variants of the Cox model (Andersen-Gill, smoothing splines) with and without a frailty effect. The AFT gamma model fit best and the estimated median time to sero-conversion in the null model was 57 days (95% confidence interval (CI): 49; 75) using all data and 47 days (95% CI: 39; 55) when only studies using experimental inoculation were considered. Some factors were consistently associated with time to sero-conversion. These included exposure by animal-to-animal contact (resulting in a seven-fold increase in time to sero-conversion compared to direct inoculation), diagnostic method to detect sero-conversion (time to sero-conversion was 1.4 times shorter when AGID was used compared to ELISA), and transmission by insect bites (biological media) delayed sero-conversion 2.3 times compared transmission via needles or other inanimate media. After fitting a frailty Cox model, results showed that sero-conversion in susceptible animals after infection using donors, in which presence of virus before the experiment started was confirmed, increased the hazard of sero-conversion two times in comparison with donors in which virus presence was not confirmed before start of the experiment. Inoculation with blood decreased the hazard 2.5 times in comparison with lymphocyte suspensions. Heterogeneity due to different research groups was also present. Finally, a Cox model with smoothing splines contained three variables: research group, route of inoculation and a non-linear spline for infective dose. In conclusion, it can be stated some factors that influence the time to sero-conversion were identified and quantified and that a moderate influence of research centre existed. These results may contribute to the estimation of the most probable times of infection in field conditions and in a better evaluation of control measures.

Animals↗

PubMed2004

Role of data aggregation in biosurveillance detection strategies with applications from ESSENCE.

INTRODUCTION: Syndromic surveillance systems are used to monitor daily electronic data streams for anomalous counts of features of varying specificity. The monitored quantities might be counts of clinical diagnoses, sales of over-the-counter influenza remedies, school absenteeism among a given age group, and so forth. Basic data-aggregation decisions for these systems include determining which records to count and how to group them in space and time. OBJECTIVES: This paper discusses the application of spatial and temporal data-aggregation strategies for multiple data streams to alerting algorithms appropriate to the surveillance region and public health threat of interest. Such a strategy was applied and evaluated for a complex, authentic, multisource, multiregion environment, including >2 years of data records from a system-evaluation exercise for the Defense Advanced Research Project Agency (DARPA). METHODS: Multivariate and multiple univariate statistical process control methods were adapted and applied to the DARPA data collection. Comparative parametric analyses based on temporal aggregation were used to optimize the performance of these algorithms for timely detection of a set of outbreaks identified in the data by a team of epidemiologists. RESULTS: The sensitivity and timeliness of the most promising detection methods were tested at empirically calculated thresholds corresponding to multiple practical false-alert rates. Even at the strictest false-alert rate, all but one of the outbreaks were detected by the best method, and the best methods achieved a 1-day median time before alert over the set of test outbreaks. CONCLUSIONS: These results indicate that a biosurveillance system can provide a substantial alerting-timeliness advantage over traditional public health monitoring for certain outbreaks. Comparative analyses of individual algorithm results indicate further achievable improvement in sensitivity and specificity.

Algorithms↗

PubMed2000

The effect of data aggregation on temporal stability of cardiovascular reactivity.

Temporal stability of behaviorally evoked cardiovascular responses is important for theoretical (concept of activation) and practical (risk for cardiovascular diseases) reasons. As in test psychology, reliability of physiological responsivity depends on the degree of data aggregation across several measurements. This paper describes a statistical approach based on intra-class correlations. This approach is suited to define certain stability measures based on variance components representing different levels of data aggregation. An empirical investigation is presented comprised of 58 subjects, three physiological parameters (heart rate, systolic and diastolic blood pressure), two mental tasks, two sequences of the tasks within one session, and 2 days with an interval of 4 weeks between them. In addition to the finding that data aggregation can generally increase stability, the different sources of aggregation (across phases within a task, across tasks, and across task sequences) and their combinations are systematically compared with regard to their contribution to this enhancement. Finally, it will be shown how the approach can be utilized to explain aggregation effects for other psychophysiological research questions such as covariation, consistency, and ambulatory assessment of cardiovascular functioning.

Adult↗

PubMed2006

Approach for qualitative validation using aggregated data for a stochastic simulation model of the spread of the bovine viral-diarrhoea virus in a dairy cattle herd.

Qualitative validation consists in showing that a model is able to mimic available observed data. In population level biological models, the available data frequently represent a group status, such as pool testing, rather than the individual statuses. They are aggregated. Our objective was to explore an approach for qualitative validation of a model with aggregated data and to apply it to validate a stochastic model simulating the bovine viral-diarrhoea virus (BVDV) spread within a dairy cattle herd. Repeated measures of the level of BVDV-specific antibodies in the bulk-tank milk (total milk production of a herd) were used to summarise the BVDV herd status. First, a domain of validation was defined to ensure a comparison restricted to dynamics of pathogen spread well identified among observed aggregated data (new herd infection with a wide BVDV spread). For simulations, scenarios were defined and simulation outputs at the individual animal level were aggregated at the herd level using an aggregation function. Comparison was done only for observed data and simulated aggregated outputs that were in the domain of validation. The validity of our BVDV model was not rejected. Drawbacks and ways of improvement of the approach are discussed.

Animals↗

PubMed1998

Unmixing aggregate data: estimating the social composition of enumeration districts.

"In this paper the authors address the problem of interpreting and classifying aggregate data sources and draw parallels between tasks commonly encountered in image processing and census analysis. Both of these fields already have a range of standard classification tools which are applied in such situations, but these are hindered by the aggregate nature of the input data. An approach to ¿unmixing' aggregate data, and thus revealing the nature of the subunit variation masked by aggregation, is introduced. This approach has already shown considerable success in Earth Observation applications, and in this paper the authors present the adaptation and application of the approach to Census small area statistics data for Southampton, Hants, [in England] revealing something of the social composition of Southampton's enumeration districts. The unmixing technique utilises an artificial neural network."

Censuses↗

PubMed2005

[Importance of registry of aggregated data on women giving birth].

OBJECTIVE: Analysis of causes of unchanging level of national perinatal mortality and identification of potential for its further decrease. DESIGN: Retrospective epidemiological analysis of aggregated data on perinatal care. SETTING: Mother and Child Care Institute, Prague 4-Podolí. METHODS: Correlation of selected national aggregated data on the level of perinatal care under current system and under influence of changing conditions for care provision. RESULTS: The analysis of some criteria of perinatal care demonstrated the influence of several contradictory processes: 1) among newborns below 2500 grams the stillbirth increased while the early neonatal mortality decreased; there was also decrease of contribution of congenital malformation in this group, 2) although there were more live born babies under 500 grams, who suffered from high mortality, their contribution to perinatal mortality was compensated by further decrease of early neonatal mortality of newborns weighing 1000-1499 grams, 3) the increasing frequency of low birthweight newborns did not influence the total perinatal mortality due to improved perinatal care. We observed the improvement of results among half of the regional perinatal centres with formerly higher early neonatal mortality figures, which represents the decrease of one of the reserves for further decrease of early neonatal mortality. There is a similar situation in centralisation of preterm deliveries--transfer in utero--which reached its maximum. Up to now we did not succeed in early referral of women with serious pregnancy complications which lead to stillbirth to perinatal centres with lower stillbirth rates. However this represents only small potential for decrease of total perinatal mortality. CONCLUSION: The 4-year stagnation of national perinatal mortality is a result of contradictory influence of improving level of care on one side and worsening of conditions on the other side. The potential for improvement under current conditions is almost exhausted.

Birth Weight↗

PubMed2005

[The multi-level Meta analysis model combining individual level data with aggregative level data].

OBJECTIVE: To explore the multi-level Meta analysis model combining individual level data with aggregative level data and its application in medicine. METHODS: The difference in respect to "decreased hemoglobin A(1c)" between treatment with roglizatone and treatment without roglizatone was obtained by combining individual level data from clinical trial of roglizatone natrium with aggregative level data from literatures. This endeavor was regarded as an example to construct the multi-level Meta analysis model combining individual level data with aggregative level data. RESULTS: The baseline hemoglobin A(1c) was 9% and the dose of drug was 4 mg per day. The average difference in "decreased hemoglobin A(1c)" between treatment with and without roglizatone was 0. 464%, with a 95% CI from 0.168% to 0.760%. CONCLUSION: In case that individual data are available, the multi-level Meta analysis model combining individual level data with aggregative level data can utilize the data resources adequately and the results obtained should be more accurate.

Data Interpretation, Statistical↗

PubMed2001

Standardization of non-aggregated data: theory and practice.

Direct standardization of rates is a classical method in epidemiology by which the relationship between confounders and variables of analysis is balanced between the samples or populations to be compared. While the method is appropriate if single variables of aggregated data sets are to be compared, it is limited with respect to handling many variables of different measurement scale, especially in primary data situations. Therefore the method of direct standardization is adapted to the analysis of non-aggregated data. Computation of not only rates but other statistics of central tendency and dispersion as well as confidence intervals hence becomes feasible. In addition it is possible to re-adjust the primary data weights in order to perform stratified analyses. A procedure to do so, based solely on the available original weights without the need for analyzing the standard population is proposed along with an extensive SAS macro. The utility allows for the rapid and standardized analysis and tabulation of large multi-variable data sets. Both the statistical and technical properties of the macro are discussed and its usage is explained as well as exemplified.

Computational Biology↗

PubMed1998

Evaluating and reporting astigmatism for individual and aggregate data.

PURPOSE: To demonstrate the proper method for evaluating and reporting astigmatism for individual and aggregate data. SETTING: University of Texas Medical School and Cullen Eye Institute, Baylor College of Medicine, Houston, Texas, USA. METHODS: The surgically induced refractive change (SIRC) was determined for three data sets of patients who have had keratorefractive (photorefractive keratectomy) or cataract surgery. To make changes in refraction comparable, vertex distances for the refractions and keratometric index of refraction were considered. Doubledangle plots and single-angle plots were then used to display the data. Polar values (cylinder and axis) were converted to a Cartesian (x and y) coordinate system to determine the mean value of the induced astigmatism for each data set. RESULTS: Doubled-angle plots clearly demonstrated the trends of induced astigmatism for each data set, and the mean value for induced astigmatism agreed exactly with the intuitive appearance of the plot. CONCLUSIONS: Converting astigmatism data to a Cartesian coordinate system allowed the correct computation of descriptive statistics such as mean values, standard deviations, and correlation coefficients. Using doubled-angle plots to display the data provides the investigator with the best method of recognizing trends in the data.

Astigmatism↗

PubMed2001

Parallel analysis of individual and aggregated data on antibiotic exposure and resistance in gram-negative bacilli.

To evaluate the potential bias of analyzing aggregated data, we separately examined antibiotic exposure and resistance data for 35,423 patients admitted to a university hospital in Utah, from both an individual-patient perspective and group-level perspective. From 1994 through 1998, use of defined daily doses (per 1000 patient-days) of fluoroquinolones, third-generation cephalosporins, ampicillin-sulbactam, and imipenem increased by 82%, 38%, and 99%, and decreased by 38%, respectively, whereas group-level resistance rates of Enterobacteriaceae or Pseudomonas species changed only minimally. However, in individual-patient-level analyses performed by multivariable proportional hazards regression, exposure to a fluoroquinolone, third-generation cephalosporin, ampicillin-sulbactam, or imipenem was a strong risk factor for resistance to fluoroquinolones (adjusted hazard ratio [AHR], 4.0; P<.001), third-generation cephalosporins (AHR, 3.5; P<.001), ampicillin-sulbactam (AHR, 2.3; P=.008), or imipenem (AHR, 5.7; P<.001), respectively. Thus, group-level and individual-patient-level analyses of antibiotic-use-versus-susceptibility relations yielded divergent results. Multicenter studies should include individual-patient-level data to elucidate more fully the relation between antibiotic exposure and resistance.

Ampicillin↗