Inspeção dos dados

Tabela descritiva

Descritives analyses. P-values calculated with ANOVA.
Overall Male Female p test
n 28382 8780 19602
peso_rake (mean (SD)) 3346.81 (3601.68) 3584.90 (4058.25) 3240.17 (3371.89) <0.001
idade_cat (%) <0.001
[15,32] 968 (3.4) 199 (2.3) 769 (3.9)
(32,46] 3420 (12.0) 816 (9.3) 2604 (13.3)
(46,60] 8367 (29.5) 2463 (28.1) 5904 (30.1)
(60,99] 15627 (55.1) 5302 (60.4) 10325 (52.7)
imc (mean (SD)) 27.22 (7.62) 27.10 (11.22) 27.27 (5.27) 0.079
quant_doe_cron (mean (SD)) 2.22 (1.36) 2.05 (1.30) 2.30 (1.38) <0.001
multimorbidade (mean (SD)) 0.65 (0.48) 0.60 (0.49) 0.67 (0.47) <0.001
quant_med_cron (mean (SD)) 2.24 (1.31) 2.10 (1.28) 2.30 (1.32) <0.001
regiao (%) <0.001
North 3838 (13.5) 1310 (14.9) 2528 (12.9)
Northeast 5889 (20.7) 1577 (18.0) 4312 (22.0)
Southeast 6711 (23.6) 2093 (23.8) 4618 (23.6)
South 7119 (25.1) 2220 (25.3) 4899 (25.0)
Central-West 4825 (17.0) 1580 (18.0) 3245 (16.6)
medic_psi (mean (SD)) 0.01 (0.09) 0.00 (0.06) 0.01 (0.10) <0.001
tempo_uso_medicamento (mean (SD)) 6.79 (7.42) 6.83 (7.55) 6.78 (7.36) 0.629
numero_vezes_medic (mean (SD)) 1.53 (1.17) 1.53 (1.12) 1.53 (1.18) 0.598

Modelo SEM considerando dados de pesquisa complexos e imputação

Warning message:
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lavaan 0.6-9 ended normally after 89 iterations

  Estimator                                         ML
  Optimization method                           NLMINB
  Number of model parameters                        20
                                                      
  Number of observations                         28382
                                                      
Model Test User Model:
                                                      
  Test statistic                               613.517
  Degrees of freedom                                 7
  P-value (Chi-square)                           0.000

Model Test Baseline Model:

  Test statistic                             27672.009
  Degrees of freedom                                15
  P-value                                        0.000

User Model versus Baseline Model:

  Comparative Fit Index (CFI)                    0.978
  Tucker-Lewis Index (TLI)                       0.953

Loglikelihood and Information Criteria:

  Loglikelihood user model (H0)            -358161.052
  Loglikelihood unrestricted model (H1)    -357854.293
                                                      
  Akaike (AIC)                              716362.103
  Bayesian (BIC)                            716527.174
  Sample-size adjusted Bayesian (BIC)       716463.614

Root Mean Square Error of Approximation:

  RMSEA                                          0.055
  90 Percent confidence interval - lower         0.052
  90 Percent confidence interval - upper         0.059
  P-value RMSEA <= 0.05                          0.009

Standardized Root Mean Square Residual:

  SRMR                                           0.033

Parameter Estimates:

  Standard errors                             Standard
  Information                                 Expected
  Information saturated (h1) model          Structured

Latent Variables:
                   Estimate  Std.Err  z-value    P(>|z|)   Std.lv  Std.all
  morbidity =~                                                            
    quant_doe_cron    1.000                                 1.063    0.803
    multimorbidade    0.409    0.003    118.695    0.000    0.435    0.921
  psy_med =~                                                              
    medic_psi         1.000                                 1.000   10.139
    tempo_s_mdcmnt    0.007    0.004      1.671    0.095    0.007    0.001

Regressions:
                   Estimate  Std.Err  z-value    P(>|z|)   Std.lv  Std.all
  morbidity ~                                                             
    psy_med           0.001    0.001      2.040    0.041    0.001    0.001
    idade             0.024    0.000     53.108    0.000    0.022    0.339
    imc               0.005    0.000      9.463    0.000    0.004    0.057

Covariances:
                   Estimate  Std.Err  z-value    P(>|z|)   Std.lv  Std.all
  idade ~~                                                                
    imc             -15.045    1.212    -12.413    0.000  -15.045   -0.074
  psy_med ~~                                                              
    idade            -0.054    0.009     -6.057    0.000   -0.054   -0.004
    imc              -0.010    0.008     -1.278    0.201   -0.010   -0.001

Intercepts:
                   Estimate  Std.Err  z-value    P(>|z|)   Std.lv  Std.all
   .quant_doe_cron    0.682    0.031     21.991    0.000    0.682    0.515
   .multimorbidade    0.021    0.012      1.758    0.079    0.021    0.045
   .medic_psi         0.010    0.001     16.780    0.000    0.010    0.100
   .tempo_s_mdcmnt    6.900    0.044    157.289    0.000    6.900    0.934
    idade            58.270    0.091    639.899    0.000   58.270    3.798
    imc              27.627    0.079    350.654    0.000   27.627    2.081
   .morbidity         0.000                                 0.000    0.000
    psy_med           0.000                                 0.000    0.000

Variances:
                   Estimate  Std.Err  z-value    P(>|z|)   Std.lv  Std.all
   .morbidity         1.000                                 0.885    0.885
    psy_med           1.000                                 1.000    1.000
    idade           235.350    1.976    119.126    0.000  235.350    1.000
    imc             176.177    1.479    119.126    0.000  176.177    1.000
   .quant_doe_cron    0.624    0.012     51.695    0.000    0.624    0.356
   .multimorbidade    0.034    0.002     17.657    0.000    0.034    0.152
   .medic_psi        -0.990    0.000 -12126.759    0.000   -0.990 -101.798
   .tempo_s_mdcmnt   54.615    0.458    119.126    0.000   54.615    1.000

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