each person is worth of respect and of being heard. is responsible for respecting and listening to...
TRANSCRIPT
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Prof. José Leopoldo Ferreira Antunes
Curso de VerãoAnálise Multinível em
Estudos Epidemiológicos
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Programa
1. Introdução: alguns conceitos2. Revisando análise de regressão3. Tipos de efeitos (randômico,
fixo ou intra, entre)4. Models (intercepto randômico,
coeficiente randômico)
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Each person•Is worth of respect and of being heard.•Is responsible for respecting and listening to others.•Is responsible for what they choose to share with the group.•Must respect the confidentiality of what others have chosen to share with the group.•Is responsible for their own decisions and actions.•Has the right to be silent on any issue.•Is allowed to change their mind.•Is allowed to make mistakes.
Our agreement Joe Gelona
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Huijts T, Perkins JM, Subramanian SV. Political regimes, political ideology, and self-rated health in Europe: a multilevel analysis. PLoS ONE 5(7): e11711.
S. V. Subramanian
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Huijts T, Perkins JM, Subramanian SV. Political regimes, political ideology, and self-rated health in Europe: a multilevel analysis. PLoS ONE 5(7): e11711.
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Desfecho = yi (medido em cadaindivíduo i)...Fator individual = xi (medido em cada indivíduo i) Fator contextual = Xj (medido em cada contexto j)
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i = indivíduo de 1 a n;j = contexto de 1 a mai,j
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Programa...
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Trabalho
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Prova
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“Consiste em integrar fatores individuais e contextuais na análise epidemiológica dos estados e condições de saúde. Fundamenta-se na percepção de que a distribuição de saúde e doença na população não pode ser apenas explicada por características individuais. É uma metodologia para analisar desfechos em relação a fatores que são avaliados em diferentes níveis (indivíduos, instituições, bairros, cidades). Seu objetivo é explicar como variáveis individuais e contextuais interagem para interferir na saúde.”
Porta M. A Dictionary of Epidemiology, 5th Ed. Oxford: Oxford University Press, 2008.
Miquel Porta
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“Integram fatores individuais e contextuais na análise
da distribuição de doenças e estados de saúde.”
“Utiliza métodos que analisam os desfechos de saúde
em relação a determinantes avaliados em diferentes
níveis, por exemplo, indivíduos, locais de trabalho,
áreas residenciais, regiões geográficas.”
Tom Snijders
Roel Bosker
Snijders TAB, Bosker RJ. Multilevel analysis: an introduction to basic and advanced multilevel modeling. London: Sage Publications; 2003.
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“A idéia de que os indivíduos podem ser influenciados por seu contexto social é uma noção chave das ciências sociais, e tem levado a muito debate e pesquisas empíricas sobre as interações entre os atributos dos grupos e os atributos dos indivíduos.”
Diez-Roux AV. Multilevel analysis in public health research. Annu Rev Public Health 2000; 21:171-92.
Ana Diez-Roux
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“A análise multinível pode ser usada para inferir os efeitos de causas individuais e de causas relativas a contextos sobre os resultados de saúde nos indivíduos. Seu campo de aplicação é vasto e pode envolver estudos de indivíduos aninhados em instituições (famílias, escolas, hospitais, locais de trabalho) ou em áreas de moradia (casas, bairros, cidades, regiões). Pode também envolver análise de dados longitudinais (medidas dos mesmos indivíduos repetidas no tempo) e estudos de meta-análise (pessoas examinadas no contexto de diferentes estudos).”
Diez-Roux AV. A glossary for multilevel analysis. J Epidemiol Community Health 2002; 56:588-94.
Ana Diez-Roux
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Goldstein H. Multilevel statistical models. 2nd ed. London: Institute of Education, Multilevel Models Project, 1999.http://www.soziologie.uni-halle.de/langer/multilevel/books/goldstein.pdf
Harvey Goldstein
“A análise multinível pode trazer um ganho ponderável para o esforço de compreensão da causalidade. Não é, entretanto uma panacéia universal. Não pode substituir teorias consistentes e bem construídas. Não pode dispensar a reflexão cuidadosa que se espera para qualquer procedimento de modelagem estatística. Ademais, essa análise introduz mais complexidade; propicia, mas não simplifica a compreensão. Modelos multiníveis são ferramentas para serem utilizadas com cuidado e ponderação.”
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Sophia Rabe-Hesketh
Outros termos para modelos multinível incluem modelos hierárquicos, modelos de
efeitos ou coeficientes randômicos, modelos de efeitos mistos, ou simplesmente modelos
mistos.
Anders Skrondal
Rabe-Hesketh S, Skrondal A. Multilevel and longitudinal modeling using Stata. 2nd ed. College Station, Tx: Stata Press: 2008.
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“Efeitos de fatores relacionados aos grupos ou áreas a que os indívíduos pertencem (por exemplo, indicadores de poluição ambiental) sobre desfechos individuais, após levar em consideração os efeitos de características individuais que podem ser relevantes como fatores de confusão. São estimados usando análise multinível.”
Porta M. A Dictionary of Epidemiology, 5th Ed. Oxford: Oxford University Press, 2008.
Miquel Porta
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“Efeitos de fatores individuais (i.e., características dos indivíduos dentro de grupos ou áreas, como a renda individual), sobre desfechos individuais, após levar em consideração os efeitos de fatores relevantes no nível dos grupos ou áreas a que esses indivíduos pertencem. São estimados usando análise multinível.”
Porta M. A Dictionary of Epidemiology, 5th Ed. Oxford: Oxford University Press, 2008.
Miquel Porta
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desfecho
fator
Neste exemplo, se a amostra é aleatória simples; não há efeito do fator sobre o desfecho…
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desfecho
fator
Se a amostra é organizada nos contextos das cores; o fator tem efeito crescente sobre o desfecho…
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desfecho
fator
Se a amostra é organizada nos contextos das cores; o fator tem efeito decrescente sobre o desfecho…
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desfecho
fator
O fator tem efeito decrescente sobre o desfecho;porém, há um efeito contextual que é crescente…
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desfecho
fator
O fator tem efeito decrescente sobre o desfecho;porém, há um efeito contextual que é crescente…
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Banco de dados Nível 1(dados individuais)
Nível 2(dados contextuais)
Tabagismo na gravidez e peso ao nascer Nascidos vivos Mães
Desempenho escolar (ENEM) e renda familiar Alunos 2º grau Escolas
Doença infecciosa e exposição ambiental Indivíduos Bairros
Fatores associados à cárie dentária Indivíduos Cidades
Fatores associados à cárie dentária Dentes Indivíduos
Tuberculose e aderência ao tratamento Pacientes Unidades de saúde
Avaliação longitudinal de um tratamento Medidas repetidas Pacientes
Meta-análise de avaliação de um tratamento Pacientes Estudos
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Qual a diferença entre análisemultínível, análise longitudinale meta-análise?
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“Análise estatística dos resultados de estudos separados, cujo objetivo é gerar um sumário quantitativo desses resultados, caso essa síntese possa ser sustentada por uma avaliação de comparabilidade entre os estudos. A integração dos resultados de diferentes estudos pode permitir encontrar padrões ou tendências gerais dos resultados encontrados. Devem ser considerados vários vieses na seleção de participantes dos estudos, detecção de casos e apresentação de resultados .”
Porta M. A Dictionary of Epidemiology, 5th Ed. Oxford: Oxford University Press, 2008.
Miquel Porta
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Rahman M, Sakamoto J, Fukui T. Bidi smoking and oral cancer: a meta-analysis. Int J Cancer 2003; 106: 600-4.
Mahbubur Rahman
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Rahman M, Sakamoto J, Fukui T. Bidi smoking and oral cancer: a meta-analysis. Int J Cancer 2003; 106: 600-4.
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Rahman M, Sakamoto J, Fukui T. Bidi smoking and oral cancer: a meta-analysis. Int J Cancer 2003; 106: 600-4.
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The Cochrane Collaboration open learning material. Publication bias.http://www.cochrane-net.org/openlearning/html/mod15-3.htm
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Revisando a análise de regressão
1.Regressão linear simples2.Regressão logística3.Regressão de Poisson4.Análise multivariada5.Análise hierárquica (modelos
conceituais)
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Y = b0 + b1*X
Regressão linear simples
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Y = b0 + b1*X + b2*Z + e
Análise multivariada
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Premissas da análisede regressão linear
1. Distribuição normal2. Homoscedasticidade
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Distribuição normal
Distribuição não normal
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HeteroscedasticidadeÉ o fenômeno estatístico que ocorre quando o modelo de hipótese matemático apresenta variâncias para Y e X (X1, X2, X3,..., Xn) que não são iguais para todas as observações.
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Antunes JLF, Waldman EA. The impact of AIDS, immigration and housing overcrowding on tuberculosis deaths in São Paulo, Brazil, 1994-1998. Soc Sci Med 2001; 52:1071-80.
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Análise bivariada
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Análise multivariada
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Análise bivariada
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1.Numa equação de regressão linear simples para salário anual, estimou-se em 3623 o coeficiente para uma variável dummy identificando sexo masculino.
a. Interprete o coeficiente estimado.
Exercícios
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1.Numa equação de regressão linear simples para salário anual, estimou-se em 3623 o coeficiente para uma variável dummy identificando sexo masculino.
a. Interprete o coeficiente estimado.b. Se a variável dummy fosse para sexo feminino, qual
seria o coeficiente?
Exercícios
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1.Numa equação de regressão linear simples para salário anual, estimou-se em 3623 o coeficiente para uma variável dummy identificando sexo masculino.
a. Interprete o coeficiente estimado.b. Se a variável dummy fosse para sexo feminino, qual
seria o coeficiente?c. O erro padrão do coeficiente para o sexo masculino foi
1912. Pode-se rejeitar a hipótese nula de que o salário médio na população seria o mesmo para os dois sexos, considerando um teste bi-caudal no nível de 5% de significância?
Exercícios
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2. Numa equação de regressão ajustando o salário anual segundo a idade, o intercepto foi estimado em –2000.
Qual o significado desse valor?
Exercícios
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2. Numa equação de regressão ajustando o salário anual segundo a idade, o intercepto foi estimado em –2000.
Qual o significado desse valor?
Como pode ser negativo, se o salário é sempre positivo?
Exercícios
![Page 65: Each person Is worth of respect and of being heard. Is responsible for respecting and listening to others. Is responsible for what they choose to share](https://reader035.vdocuments.net/reader035/viewer/2022062819/570638501a28abb8238f88f4/html5/thumbnails/65.jpg)
3. Em um programa de avaliação da compreensão de textos (em inglês) por crianças, a diferença de escores entre as que falam inglês em casa e as que não falam foi 63, com erro padrão de 10. Quando controlada por condição socioeconômica, a diferença ajustada entre os escores foi estimada em 49, com erro padrão de 10.a.O que significa controlar ou ajustar por condição
socioeconômica?
Exercícios
![Page 66: Each person Is worth of respect and of being heard. Is responsible for respecting and listening to others. Is responsible for what they choose to share](https://reader035.vdocuments.net/reader035/viewer/2022062819/570638501a28abb8238f88f4/html5/thumbnails/66.jpg)
3. Em um programa de avaliação da compreensão de textos (em inglês) por crianças, a diferença de escores entre as que falam inglês em casa e as que não falam foi 63, com erro padrão de 10. Quando controlada por condição socioeconômica, a diferença ajustada entre os escores foi estimada em 49, com erro padrão de 10.a.O que significa controlar ou ajustar por condição
socioeconômica?b.Por que o ajuste por uma variável “z” altera o
coeficiente de regressão que indica o efeito da variável “x” sobre a variável “y”?
Exercícios
![Page 67: Each person Is worth of respect and of being heard. Is responsible for respecting and listening to others. Is responsible for what they choose to share](https://reader035.vdocuments.net/reader035/viewer/2022062819/570638501a28abb8238f88f4/html5/thumbnails/67.jpg)
3. Em um programa de avaliação da compreensão de textos (em inglês) por crianças, a diferença de escores entre as que falam inglês em casa e as que não falam foi 63, com erro padrão de 10. Quando controlada por condição socioeconômica, a diferença ajustada entre os escores foi estimada em 49, com erro padrão de 10.a.O que significa controlar ou ajustar por condição
socioeconômica?b.Por que o ajuste por uma variável “z” altera o
coeficiente de regressão que indica o efeito da variável “x” sobre a variável “y”?
c.Como explicar a mudança no exemplo acima, atentando para o sentido da diferença entre os valores?
Exercícios
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4. Considere a seguinte equação de regressão explicando os salários de uma empresa:
Y=30000+2000*masc+600*anos_exp–100*masc*anos_exp
a. Interprete cada coeficiente que foi estimado.
Exercícios
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4. Considere a seguinte equação de regressão explicando os salários de uma empresa:
Y=30000+2000*masc+600*anos_exp–100*masc*anos_exp
a. Interprete cada coeficiente que foi estimado.
b. Qual é a diferença entre o salário médio na população, entre homens e mulheres que têm 10 anos de experiência?
Exercícios
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5. No exercício anterior, a equação de regressão continha um termo de interação entre “anos de experiência” e “sexo masculino” :
Y=30000+2000*masc+600*anos_exp–100*masc*anos_exp
Como se constrói uma variável para discriminar o termo de interação?
Exercícios
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