Statistical Analysis

Because the allocation of constant Parameters was skewed, flat data were informed utilizing commonness and percentage, while continuous variables were characterized using the median and interquartile degree. The effect of COVID-19 on the mental health of the older people was investigated using a linear mix model for loneliness and a mixed logistic standard for depression, anxiety, and frailty, meaning that after reshaping the data into a “long” format, we used linear mix model for loneliness outcome which is a continuous variable, and Since frailty, depression, and anxiety are binary variables, we used mixed logistic models. By multiplying the COVID-19 circumstance period and the indicated factors in the hybrid models, the interaction impact among gender, age, education, comorbidity, living independently, and Corona circumstance was also evaluated. The loneliness result was quantile adjusted to produce a conventional normal distribution after reshaping the data into a “long” format. For normalized loneliness, the data is first transformed to a percentile (fractional) level. The computed coefficients are interpreted as a common mean contrast using the typical normal allocation quantile operation.