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Academic literature on the topic 'Biais dans les réponses – Enquêtes'
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Journal articles on the topic "Biais dans les réponses – Enquêtes"
Helfer, Jean-Pierre, and Michel Kalika. "La cohérence interne dans les enquêtes par interviews." Recherche et Applications en Marketing (French Edition) 3, no. 1 (1988): 1–14. http://dx.doi.org/10.1177/076737018800300101.
Full textGardhouse, Christine, Matt Hurst, Sujani Sivanantharajah, and Nadia Ciampa. "Utilisation d’un sondage en ligne pour la collecte de renseignements sur l’exposition aux aliments, sous-étude Foodbook, de février à avril 2015." Relevé des maladies transmissibles au Canada 47, no. 1 (2021): 27–34. http://dx.doi.org/10.14745/ccdr.v47i01a05f.
Full textPapuchon, Adrien. "Ce qu’Alis nous dit de ses amis. L’effet de désirabilité sociale et sa variabilité au prisme de questions portant sur une prestation sociale fictive." Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique 137-138, no. 1 (2018): 120–39. http://dx.doi.org/10.1177/0759106318761563.
Full textDe Faviis, Giulia. "Liaison et conscience phonologique en Côte d’Ivoire : analyse des réponses épi- et métaphonologiques face à un test d’acceptabilité administré aux adultes abidjanais." SHS Web of Conferences 78 (2020): 10007. http://dx.doi.org/10.1051/shsconf/20207810007.
Full textDesroches, Mireille, Liza Lee, Shamir Mukhi, and Christina Bancej. "Représentativité du programme participatif de surveillance des maladies ActionGrippe, 2015–2016 à 2018–2019 : comment les participants se comparent-ils à la population canadienne?" Relevé des maladies transmissibles au Canada 47, no. 09 (2021): 401–9. http://dx.doi.org/10.14745/ccdr.v47i09a03f.
Full textBoulbry, Gaëlle. "Enquêtes verbales et biais méthodologiques Le cas des seniors et de leurs non-réponses." La Revue des Sciences de Gestion, Direction et Gestion, no. 222 (December 2006): 69–78. http://dx.doi.org/10.1051/larsg:2006058.
Full textLaffont, Sophie, Eve Blanquart, and Jean-Charles Guéry. "Biais de sexe dans l’asthme allergique." médecine/sciences 34, no. 3 (2018): 247–52. http://dx.doi.org/10.1051/medsci/20183403013.
Full textBergouignan, Christophe. "Recourir aux microsimulations pour étudier la mortalité de crise : illustration par la mortalité au Burundi en 1993." Cahiers québécois de démographie 40, no. 2 (2012): 299–329. http://dx.doi.org/10.7202/1011543ar.
Full textBielska, I. A., H. Ouellette-Kuntz, and D. Hunter. "Utilisation d'enquêtes nationales pour la surveillance de la santé mentale des personnes présentant une déficience intellectuelle au Canada." Maladies chroniques et blessures au Canada 32, no. 4 (2012): 216–22. http://dx.doi.org/10.24095/hpcdp.32.4.03f.
Full textJanson, Harald. "Examiner Effect on Number of Rorschach Responses at Current and Later Occasions." Rorschachiana 23, no. 1 (1999): 28–42. http://dx.doi.org/10.1027/1192-5604.23.1.28.
Full textDissertations / Theses on the topic "Biais dans les réponses – Enquêtes"
Allodehou, Amos. "Pouvoir prédictif des questions de sondage." Master's thesis, Université Laval, 2015. http://hdl.handle.net/20.500.11794/26070.
Full textSantin, Gaëlle. "Non-réponse totale dans les enquêtes de surveillance épidémiologique." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA11T007/document.
Full textNonresponse occurs in most epidemiologic surveys and may generate selection bias (which is, in this case, a nonresponse bias) when it is linked to outcome variables. In epidemiologic surveillance, whose one of the purpose is to estimate prevalences, it is usual to use survey sampling. In this case, unit nonresponse occurs and it is possible to use methods coming from survey sampling to correct for nonresponse. Nonresponse bias can be expressed as the product of the inverse of the response rate and the covariance between the probability of response and the outcome variable. Thus, two options are available to reduce the effect of nonresponse. The first is to increase the response rate by developing appropriate strategies at the study design phase. However, the maximization of the response rate can prompt other kinds of bias, such as measurement bias. In the second option, after data collection, information associated with both nonresponse and the outcome variable, and available for both respondents and nonrespondents, can be used to calculate corrective factors. This solution requires having information on the complete random sample (respondents and nonrespondents); but this information is rarely sufficient. Recent possibilities to access administrative databases (particularly those pertaining to health insurance) offer new perspectives on this aspect.The objectives of this work focused on the nonresponse bias were to study the contribution of supplementary data (administrative databases and complementary survey among nonrespondents) and to discuss the influence of the response rate on the nonresponse error and the measurement error. The analyses focused on occupational health epidemiologic surveillance, using data (at inclusion) from the Coset-MSA cohort pilot study. In this study, in addition to the data collected by questionnaire (initial and complementary survey among nonrespondents), auxiliary information from health and occupational administrative databases was available for both respondents and nonrespondents.Results show that the data from the initial survey (response rate : 24%), corrected for nonresponse with information directly linked to the study subject (health and work) produce estimations of prevalence close to those obtained by combining data from the initial survey and the complementary survey (response rate : 63%), after nonresponse adjustment on the same auxiliary information. Using a complementary survey to attain a maximal response rate does not seem to be necessary in order to decrease nonresponse bias. Nevertheless, this study highlights potential measurement bias which could be more consequential for the initial survey than for the complementary survey. The specific study of the trade-off between nonresponse error and measurement error shows that, for the studied variables and after correction for nonresponse, the sum of the nonresponse error and the measurement error is equivalent in the initial survey and in the combined surveys (initial plus complementary survey). This work illustrated the potential of administrative databases for decreasing the nonresponse error and for evaluating measurement error in an epidemiologic surveillance survey
Marceau, Claudia. "Analyse de l'influence des biais de réponse sur les résultats à l'inventaire de personnalité NEO (NEO-PI-R)." Thesis, Université Laval, 2012. http://www.theses.ulaval.ca/2012/29528/29528.pdf.
Full textYaméogo, Nadège-Désirée. "Analyse de la demande résidentielle d'électricité à partir d'enquêtes indépendantes : correction de biais de sélection et d'endogénéité dans un contexte de classes latentes." Doctoral thesis, Université Laval, 2008. http://hdl.handle.net/20.500.11794/19745.
Full textGiguère, Katia. "Mesure objective des rapports sexuels non protégés et caractérisation du sous-rapportage des rapports non protégés chez les travailleuses du sexe au Bénin à l'aide de marqueurs biologiques de l'exposition au sperme." Doctoral thesis, Université Laval, 2018. http://hdl.handle.net/20.500.11794/34010.
Full textUnprotected sex (UPS) is a major risk factor for human immunodeficiency virus (HIV) infection and must be measured as validly as possible in HIV prevention studies. To date, the questionnaire is the most commonly used tool to assess sexual behaviours. However, self-report of sexual behaviours is subject to recall and desirability biases. The use of biomarkers of recent semen exposure might help to overcome these biases. Prostatespecific antigen (PSA) and Y chromosomal DNA (Yc-DNA) are the most characterized biomarkers of semen exposure. PSA and Yc-DNA can be detected up to two and 14 days following UPS. Over the course of an early antiretroviral therapy (E-ART) and pre-exposure prophylaxis (PrEP) demonstration study that was conducted among professional female sex workers (FSW) in Cotonou, Benin, under-reporting of UPS was expected, as well as a change in UPS in the PrEP group. Our objectives were thus to validate self-report of UPS by the means of PSA and Yc-DNA detection; to compare under-reporting of UPS over the last two and 14 days; and to assess trends in UPS in the PrEP group. We also aimed to compare the UPS detection capability of a novel screening test of Yc-DNA, a nested polymerase chain reaction targeting the testis-specific protein Y-encoded family of homologous genes (n-TSPY), to six other commonly used methods to detect recent semen exposure. At baseline of the E-ART/PrEP study and over a 24 months period of follow-up, UPS from the last two and 14 days were assessed every six months by questionnaire and by PSA and Yc-DNA screening. Under-reporting of UPS in the last two or 14 days was defined as reporting no UPS in the last two or 14 days while testing positive for PSA or Yc-DNA, respectively. A robust Poisson regression was used to compare under-reporting over the last two and 14 days. Trends in UPS as measured with the different tools were assessed by the means of a log-binomial regression. Generalized estimating equations (GEE) were used to account for dependence between observations. At baseline, we observed about 20% of under-reporting of UPS among FSW from Cotonou. However, we observed no statistically significant difference between under-reporting in the last two days and under-reporting in the last 14 days. Some of our results suggest that the relative performances of each biomarker to detect UPS over its corresponding recall period are not equal, which might have prevented us to detect a difference in under-reporting over the two recall periods. No trend in UPS was observed in the PrEP group. Finally, using n-TSPY as a reference test, each of six commonly used methods to detect recent semen exposure lacked sensitivity in the detection of RSNP. In conclusion, self-report of UPS is biased and must be cautiously interpreted. A better characterization of the clearance of PSA and Yc-DNA is required in order to better evaluate the potential effect of the recall period length on under-reporting of UPS. The absence of any evidence of a trend in UPS in the PrEP group might suggests that there was no risk compensation over the PrEP demonstration study and that PrEP might be a suitable HIV prevention method to use among FSW. Our trends in UPS analyses also pointed out the necessity to objectively assess UPS by the means of biomarkers and to correct for the potential selection bias when assessing trends in UPS over the course of a longitudinal study with high attrition. Finally, the n-TSPY might be of great utility to detect UPS in observational studies where many factors might accelerate the clearance of the biomarkers.
Perrin, Olivier. "Des énigmes de la recherche d'information : contribution à l'analyse du couple question-réponse dans le processus d'échec documentaire chez les professionnels de l'information." Phd thesis, Université Paris VIII Vincennes-Saint Denis, 2013. http://tel.archives-ouvertes.fr/tel-01022475.
Full textBérard-Chagnon, Julien. "L'attrition dans les enquêtes sociales longitudinales : le cas de l'Étude longitudinale du développement des enfants du Québec (ÉLDEQ)." Thèse, 2007. http://hdl.handle.net/1866/7715.
Full textLespérance, Anne-Marie. "Analyse acoustique de la conviction exprimée dans des réponses de sondage : un raffinement des enquêtes téléphoniques." Thèse, 2014. http://hdl.handle.net/1866/11629.
Full textSurveys by phone usually involve the recording of responses in terms of their literal linguistic content ("yes", "never", politician name, etc.). However, oral responses also possess acoustic aspects that express a degree of conviction of respondents. In current survey techniques, this "extralinguistic" information is not considered although it can be used to predict the respondent’s behavior. This paper aims to demonstrate that acoustic measures of the conviction expressed by respondents can be used to improve the prediction of behaviors as estimated by survey techniques. This demonstration is done in two steps involving two experiments. Experiment 1, conducted in a laboratory setting (n = 25), was designed to isolate the vocal variables associated with the expression of the conviction. This first test served to isolate the relevant measurable variables and "categorical" values that could be used to categorize oral responses. Experiment 2 involved the application of these acoustic measures in the analysis of responses recorded during a pre-election telephone survey conducted by Leger in 2010 (a corpus of 400 interviews). This second experiment showed that a categorization of oral responses (n = 188) based on the basis of values of expressed conviction (as defined in Experiment 1) can improve the prediction of the behavior of voters. The results suggest that oral-survey responses contain measurable acoustic cues that express a degree of conviction, which can be associated with a willingness to produce certain behaviors. The nature of the variables also presents the possibility of an automatic detection. The nature of the variables also presents the possibility of an automatic detection.
Dongmo, Jiongo Valéry. "Inférence robuste à la présence des valeurs aberrantes dans les enquêtes." Thèse, 2015. http://hdl.handle.net/1866/13720.
Full textThis thesis focuses on the treatment of representative outliers in two important aspects of surveys: small area estimation and imputation for item non-response. Concerning small area estimation, robust estimators in unit-level models have been studied. Sinha & Rao (2009) proposed estimation procedures designed for small area means, based on robustified maximum likelihood parameters estimates of linear mixed model and robust empirical best linear unbiased predictors of the random effect of the underlying model. Their robust methods for estimating area means are of the plug-in type, and in view of the results of Chambers (1986), the resulting robust estimators may be biased in some situations. Biascorrected estimators have been proposed by Chambers et al. (2014). In addition, these robust small area estimators were associated with the estimation of the Mean Square Error (MSE). Sinha & Rao (2009) proposed a parametric bootstrap procedure based on the robust estimates of the parameters of the underlying linear mixed model to estimate the MSE. Analytical procedures for the estimation of the MSE have been proposed in Chambers et al. (2014). However, their theoretical validity has not been formally established and their empirical performances are not fully satisfactorily. Here, we investigate two new approaches for the robust version the best empirical unbiased estimator: the first one relies on the work of Chambers (1986), while the second proposal uses the concept of conditional bias as an influence measure to assess the impact of units in the population. These two classes of robust small area estimators also include a correction term for the bias. However, they are both fully bias-corrected, in the sense that the correction term takes into account the potential impact of the other domains on the small area of interest unlike the one of Chambers et al. (2014) which focuses only on the domain of interest. Under certain conditions, non-negligible bias is expected for the Sinha-Rao method, while the proposed methods exhibit significant bias reduction, controlled by appropriate choices of the influence function and tuning constants. Monte Carlo simulations are conducted, and comparisons are made between: the new robust estimators, the Sinha-Rao estimator, and the bias-corrected estimator. Empirical results suggest that the Sinha-Rao method and the bias-adjusted estimator of Chambers et al (2014) may exhibit a large bias, while the new procedures offer often better performances in terms of bias and mean squared error. In addition, we propose a new bootstrap procedure for MSE estimation of robust small area predictors. Unlike existing approaches, we formally prove the asymptotic validity of the proposed bootstrap method. Moreover, the proposed method is semi-parametric, i.e., it does not rely on specific distributional assumptions about the errors and random effects of the unit-level model underlying the small-area estimation, thus it is particularly attractive and more widely applicable. We assess the finite sample performance of our bootstrap estimator through Monte Carlo simulations. The results show that our procedure performs satisfactorily well and outperforms existing ones. Application of the proposed method is illustrated by analyzing a well-known outlier-contaminated small county crops area data from North-Central Iowa farms and Landsat satellite images. Concerning imputation in the presence of item non-response, some single imputation methods have been studied. The deterministic regression imputation, which includes the ratio imputation and mean imputation are often used in surveys. These imputation methods may lead to biased imputed estimators if the imputation model or the non-response model is not properly specified. Recently, doubly robust imputed estimators have been developed. However, in the presence of outliers, the doubly robust imputed estimators can be very unstable. Using the concept of conditional bias as a measure of influence (Beaumont, Haziza and Ruiz-Gazen, 2013), we propose an outlier robust version of the doubly robust imputed estimator. Thus this estimator is denoted as a triple robust imputed estimator. The results of simulation studies show that the proposed estimator performs satisfactorily well for an appropriate choice of the tuning constant.