Sas enterprise guide 8

Categorical variables are presented as counts and relative frequencies. Continuous variables are presented as mean and standard deviation (SD) or 95% confidence intervals (CI) if evenly distributed and as median with interquartile range (IQR) if skewed. We analyzed the mothers’ NPI I and II total scores, score differences between NPI I and NPI II and the scores of the six sub-categories crying, feeding, spitting, elimination, sleeping and predictability. For the main outcomes (NPI I and II and NPI score difference), mean and 95% CIs were calculated. To adjust for differences in NPI I, an analysis of covariance was carried out as a sensitivity analysis using a generalized linear model.
Effect sizes were calculated according to Cohen [Cohen’s d = (M₂ − M₁)/SD_pooled] in order to provide an objective estimation of the strength of effect in addition to the crude and adjusted means. The relative “risk” (= probability) of having a positive direction in the perception of the own baby compared to average babies between the two groups was calculated using an unadjusted linear model.
SAS Enterprise Guide 8.4 (SAS Institute Inc., Cary, NC, United States) was used to perform statistical analyses and produce figures.

SAS Enterprise Guide 8.4 (SAS Institute Inc., Cary, NC, USA) was used to perform statistical analyses and produce figures.

Continuous variables are presented as median with interquartile range (IQR) if skewed and mean with confidence intervals (CI) if normally distributed. Discrete variables are presented as counts and relative frequencies. SAS Enterprise Guide 8.4 (SAS Institute Inc., Cary, NC, USA) was used to perform statistical analyses and produce figures. Effect sizes to compare mean differences (T1 − T2) between the control and intervention groups were calculated according to Cohen using pooled weighted standard deviations.

Anonymized clinical data were extracted from discharge summaries. Data were entered online into a questionnaire hosted at Microsoft Office Forms 365 for institutional users by the participating centers themselves. Alternatively, anonymized discharge letters were mailed or emailed to the principal study site (Department of Pediatrics I, University Medicine Essen) and entered by local staff (LW and KH) (Figure 1). After the completion of data collection, the raw data were downloaded as a Microsoft Office Excel file and imported into SAS Enterprise Guide 8.4 for statistical analyses.
To determine the percentage of PICU capacities represented by the participating centers, we accessed the DIVI registry of intensive care beds (German Interdisciplinary Association of Intensive Care and Emergency Medicine, Deutsche interdisziplinäre Vereinigung für Intensiv- und Notfallmedizin) and extracted the total number of PICUs, PICU beds in Germany and the number of beds provided by the participating centers in this study. Some children’s hospitals do not report pediatric and neonatal intensive care capacities separately in the DIVI registry. These capacities were ignored for the calculation of the percentage, since we assumed that this is information is missing completely at random.

Continuous variables are presented as median with interquartile range (IQR) and mean with 95% confidence intervals (CI). For discrete variables, absolute and relative frequencies are given. Standardized morbidity ratios (SMR) for the lockdown period were calculated, adjusting for age and sex. The years from 2017 to 2019 served as reference period to calculate the expected number of cases for 2020. The observed number of cases in 2020 was then divided by the expected number of cases. An SMR > 1 indicates an increase in cases, an SMR < 1 a decrease. We calculated exact 95% CIs if the number of observed events in the lockdown period was <15 and employed the Poisson approximation to calculate CIs in case of ≥15 events [8 (link)]. Additionally, p-values were calculated for all SMRs.
Age groups for calculation of SMRs were defined as 0–1 years, 2–5 years, 6–11 years, and 12–17 years. Three patients with diverse gender, all from the reference period, were excluded from SMR calculations since no patient with diverse gender was admitted during the observation period.
SAS Enterprise Guide 8.4 (SAS Institute Inc., Cary, NC, USA) was used to perform statistical analyses and produce figures. SISA software [9 ] was used to calculate exact and Poisson CIs for SMRs.

SAS Enterprise Guide 8.4 (SAS Institute Inc., Cary, NC, USA) was used to perform statistical analyses and produce figures.