Estatística, Análise Matemática e Optimización
http://hdl.handle.net/10347/2918
2024-03-29T08:45:32ZGoodness-of-fit tests in proportional hazards models with random effects
http://hdl.handle.net/10347/33372
Goodness-of-fit tests in proportional hazards models with random effects
González Manteiga, Wenceslao; Martínez Miranda, María Dolores; Keilegom, Ingrid van
This paper deals with testing the functional form of the covariate effects in a Coxproportional hazards model with random effects. We assume that the responsesare clustered and incomplete due to right censoring. The estimation of the modelunder the null (parametric covariate effect) and the alternative (nonparametriceffect) is performed using the full marginal likelihood. Under the alternative, thenonparametric covariate effects are estimated using orthogonal expansions. Thetest statistic is the likelihood ratio statistic, and its distribution is approximatedusing a bootstrap method. The performance of the proposed testing procedureis studied through simulations. The method is also applied on two real data setsone from biomedical research and one from veterinary medicine.
2023-01-01T00:00:00ZTesting similarity between first-order intensities of spatial point processes. A comparative study
http://hdl.handle.net/10347/33370
Testing similarity between first-order intensities of spatial point processes. A comparative study
Fuentes-Santos, Isabel; González Manteiga, Wenceslao; Mateu, Jorge
Testing whether two spatial point processes have the same spatial distribution is an important task that can be addressed from different perspectives.
A Kolmogorov-Smirnov test with asymptotic calibration and a Cramer von Mises type test with bootstrap calibration have recently been developed to compare the first-order intensity of two observed patterns. Motivated by common practice in epidemiological studies, we introduce a regression test based on the relative risk function with two alternative bootstrap calibrations.
This paper compares the performance of these nonparametric tests through both an intensive simulation study, and the application to wildfire and crime data. The three tests provide good calibrations of the null hypothesis for simulated Poisson and non-Poisson spatial point processes,
but the Cramer von Mises and regression tests outperform the costefficient Kolmogorov-Smirnov test in terms of power. In the real data analysis we have seen that the Kolmogorov-Smirnov test does not detect differences between spatial point patterns when dealing with sparse data. In view of these results, it would be preferable using the Cramer von Mises
or regression tests despite their higher computational demand.
2023-01-01T00:00:00ZA consistent test of equality of distributions for Hilbert-valued random elements
http://hdl.handle.net/10347/33344
A consistent test of equality of distributions for Hilbert-valued random elements
González Rodríguez, Gil; Colubi Cervero, Ana; González-Manteiga, Wenceslao; Febrero Bande, Manuel
Two independent random elements taking values in a separable Hilbert space are considered.
The aim is to develop a test with bootstrap calibration to check whether they have the same
distribution or not. A transformation of both random elements into a new separable Hilbert
space is considered so that the equality of expectations of the transformed random elements is
equivalent to the equality of distributions. Thus, a bootstrap test procedure to check the equality
of means can be used in order to solve the original problem. It will be shown that both the
asymptotic and bootstrap approaches proposed are asymptotically correct and consistent. The
results can be applied, for example, in functional data analysis. In practice, the test can be solved
with simple operations in the original space without applying the mentioned transformation,
which is used only to guarantee the theoretical results. Empirical results and comparisons with
related methods support and complement the theory.
2024-01-01T00:00:00ZAssociation analysis between symptomology and herpesvirus IgG antibody concentrations in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and multiple sclerosis
http://hdl.handle.net/10347/33343
Association analysis between symptomology and herpesvirus IgG antibody concentrations in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and multiple sclerosis
Domingues, Tiago; Ameijeiras Alonso, José; Sepúlveda, Nuno
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and multiple sclerosis (MS) are two complex and multifactorial diseases whose patients experience persistent fatigue, cognitive impairment, among other shared symptoms. The onset of these diseases has also been linked to acute herpesvirus infections or their reactivations. In this work, we re-analyzed a previously-described dataset related to IgG antibody responses to 6 herpesviruses (CMV – cytomegalovirus; EBV – Epstein-Barr virus; HHV6 – human herpesvirus-6; HSV1 and HSV2 – herpes simplex virus-1 and -2, respectively; VZV – varicella-zoster virus) from the United Kingdom ME/CFS biobank. The primary goal was to report the underlying symptomology and its association with herpesvirus IgG antibodies using data from 4 disease-trigger-based subgroups of ME/CFS patients (n = 222) and patients with MS (n = 46). The secondary objective was to assess whether serological data could distinguish ME/CFS and its subgroup from MS using a SuperLearner (SL) algorithm. There was evidence for a significant negative association between temporary eye insight disturbance and CMV antibody concentrations and for a significant positive association between bladder problems and EBV antibody concentrations in the MS group. In the ME/CFS or its subgroups, the most significant antibody-symptom association was obtained for increasing HSV1 antibody concentration and brain fog, a finding in line with a negative impact of HSV1 exposure on cognitive outcomes in both healthy and disease conditions. There was also evidence for a higher number of significant antibody-symptom associations in the MS group than in the ME/CFS group. When we combined all the serological data in an SL algorithm, we could distinguish three ME/CFS subgroups (unknown disease trigger, non-infection trigger, and an infection disease trigger confirmed in the lab at the time of the event) from the MS group. However, we could not find the same for the remaining ME/CFS group (related to an unconfirmed infection disease). In conclusion, IgG antibody data explains more the symptomology of MS patients than the one of ME/CFS patients. Given the fluctuating nature of symptoms in ME/CFS patients, the clinical implication of these findings remains to be determined with a longitudinal study. This study is likely to ascertain the robustness of the associations during natural disease course.
2023-01-01T00:00:00Z