Question

Develop your own definition for cross-sectional statistics and longitudinal statistical measurements. After you have done that then compare and contrast them. Along that line discuss the strengths and weaknesses of both. Which do you favor? Why?

Answer 1

Let us first of all try to understand as to what a cross sectional statistics is and what exactly is a longitudinal statistical measurements.

To begin with, a cross sectional statistics is a statistical analysis or study of a dataset from a given population or its subset in/at a given period of time. For example - time series of observational data in a given experiment. Another example of it can be a capturing of means of long jump distances of two groups of athletes from different universities over a given period of time and then to compare their means to check if their differences are significant or not.

A longitudinal study on the other hand refers to the analysis where the outcomes of output from the sampler /participant and possibly the treatments or exposures are collected over various follow-up times.A longitudinal study generally yields multiple or \repeated" measurements on each subject.

For example,Key bosy parameters of Cancer patients of a given hospital may be followed over time and monthly measures are collected to characterize immune status and disease burden respectively.

These body parameters are then referenced and the data are correlated within subjects and thus require special statistical techniques for valid analysis and inference.

Differences

The key to understanding the difference between cross-sectional statisitcs and longitudinal studies is

1. time and

2. the amount of measurements required.

Usually since a cross sectional statistics involves real time capturing of time based data ,it is much easier and quicker to perform in case one needs to solve a research question here and now.  

For example , let us assume that a given population has a specific outcome (i.e. a disease) and now we want to find out if a certain exposure (i.e. drinking) could cause that outcome. So to ascertian this, a cross-sectional statisitcal analysis will only require one contact to the patients/persons with the outcome to find out if the person is exposed or not.

Now look at the longitudinal studies. The longitudinal study will require a constant follow-up for the same validation of outcome owing ot certain factor (i.e drinking). A number of exposures are measured at baseline and from there we need to observe the population for the outcome.

Strengths and weaknesses

The cause and effect analysis /validation is much more reliable in a longitudinal study. However, it is marred by lack of real time data over a long time and are therefore reported less frequently.

A cross-sectional statistics on the other hand have a very long sampling period. That means that it can take a long time to sample the amount of people required to make statistical analyses. This is the case when the outcome of interest is infrequent in the population. But the people included in the study are not followed over time.

Usually the use of cross-sectional statistics refers to the researcher decision based on SHORTAGE of TIME.

A longitudinal statistical design is stronger and effective than the cross sectional design because it incorporates a longer samplimg over long period of time and hence it has stronger in establishing changes over time, relationships, casuality..etc.

Thus between the two, the longitudinal statistical measurmeents should be chosen since it gives us a better understanding of the causal relationship of the data points over time .