From January 18 to August 29 2017, consecutive children who had received the 4-dose course of PCV13, as per the National Immunization Program recommendations, were prospectively enrolled through 45 general pediatric practice facilities in 30 municipalities in Greece. A single oropharyngeal sample was obtained from each subject in a standardized manner (questionnaire, procedure).
Based on the time interval since the fourth dose of PCV13, the children sampled were grouped for analysis in 6 groups: 26 days to 11 months (m); 12-23 m; 24-35 m; 36-47 m; 48-59 m and 60-71 m. (column E).
Carriage and distribution of Streptococcus pneumoniae serotypes was detected by RT-PCR (Column J to N). Blank cells
Demographics (Columns B and C)
Confounding factors (Columns F and I)
Create 7 different files with results as the attached list of rtf files. Macros should be used (or any other programing approach) to perform repeated tasks
File |
Description |
SAS procedure |
1 |
Demographics by total colonization including table footnotes |
Customized program, choose your own approach |
2 |
table of distributions of confounders and Grouping and graphs |
Proc tabulate and proc gplot |
3 |
Logistic regression where Grouping is an ordinal variable (1, 2, 3, 5, 6) for column J
Rows with confounders missing are excluded |
proc logistic data=XX; class XX (param=ref); model XX (event=' XX ')= XX / scale=none clparm=wald clodds=pl rsquare; where XX ne ' XX '; run; |
4 |
Logistic regression where Grouping is an ordinal variable (1, 2, 3, 5, 6) for column K
Rows with confounders missing are excluded |
As above |
5 |
Logistic regression where Grouping is an ordinal variable (1, 2, 3, 5, 6) for column L
Rows with confounders missing are excluded |
As above |
6 |
Logistic regression where Grouping is an ordinal variable (1, 2, 3, 5, 6) for column M
Rows with confounders missing are excluded |
As above |
7 |
Logistic regression where Grouping is an ordinal variable (1, 2, 3, 5, 6) for column N
Rows with confounders missing are excluded. |
As above |
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