Sunday, December 18, 2011

Difference between error and residual ...

Error is the difference between the observed value in a sample/subject and the true value in the population (which is actually not known).
whereas Residual is the difference between the observed value and the predicted (or estimated value) from our regression equations.
So, even they may sound quite similar but are actually quite different. In regression, we have to be very careful about the residual diagnostics. They are very vital.

Monday, December 5, 2011

Maternal mortality rate .... Is it the same as Maternal mortality ratio ?

No, Maternal mortality rate is the number of maternal deaths per 1000 women in the reproductive age group. Whereas Maternal mortality ratio is the number of maternal deaths per 1 lac live births. These two are different measures.
Source: link is

Saturday, December 3, 2011

p-value and confidence interval

p - value is used in hypothesis testing. It reveals the probability of 'chance' to be responsible for the difference. The less the p value the less the probability that the difference is due to chance. Conventionally, a cut off of 5% or 0.05 or one in twenty is considered for saying that there is a statistically significant difference. But, always keep in mind that the difference in 0.049 and 0.051 is not great. The probability that the difference is due to chance is 4.9% and 5.1% respectively in the example given in the earlier line. So they are telling nearly the same story. But going by our cutoff of 5%, one is statistically significant and the other is statistically not significant. Human judgement, common sense and experience should prevail for interpretation of the result. One more word of caution: Increasing the sample size tends to magnify the differences and chances for finding a statistically significant difference increases.

95% Confidence interval arrived from our sample is the probability that the population value lies in that interval 95% of the time. The condition is that the sample should be representative of the population.

Tuesday, November 29, 2011

Difference between Covariance and Correlation

Both measure the same thing, nearly the same to be more accurate. Covariance measures how the two variables are related. A positive value indicates a positive linear relationship. In R software, it can be calculated by cov(variable x, variable y).
Correlation coefficient is covariance divided by the product of the standard deviations of the two variables. It is a normalized measurement of the relationship between two variables.If it is near to one means that there is a positive linear relationship. If '-1' means that negative linear relationship. If zero, it means no linear relationship. In R software, it can be calculated simply by cor(variable x, variable y)

Wednesday, September 28, 2011

Japanese Encephalitis reported for the first time in Delhi

A disease which was till now thought to be limited to Eastern UP has been reported from Delhi. Epidemiological investigations are ongoing. Lab reports from NCDC have confir med JE antibodies from the samples that were sent from suspected patients.

 If local transmission is confirmed, Delhi will have to gear up to take care of one more scourge: Culex tritaenorynchus. This will be in addition to the existing burden of other mosquito borne diseases like Malaria and Dengue, which cause deadly outbreaks in Delhi. It is hightime that sanitation is given a high priority in the capital city of India.

Thursday, July 14, 2011

Levene's test for equality of variances

In an earlier post, I discussed about Bartlett's test for homogeneity of variances. But I found out that Bartlett's test is very sensitive to normality assumption. Even if the data is slightly non-normal, then it does not hold good. In that case Levene's test for equality of variances becomes the test of choice.

In R we can go for library(car) and then apply Levene's Test by using the following formula:
leveneTest(age~sex): in this e.g. sex is a categorical variable having male and female as two groups. This formula will test the null hypothesis that the variances of age in male and female groups are equal. If p is less than 0.05 then it means that the null hypothesis is rejected i.e. the variances are not equal in the two groups.

Friday, June 24, 2011

Test for homogeneity of variance: Bartlett test

First an important assumption: that the normal distribution is followed by the data.
Null hypothesis for this test is that the variances are equal in the groups.
So if, p value less than 0.05, null hypothesis is rejected and interpretation being that the variances are not equal (or homodescacity is absent).

In case, the normality assumption is violated, then we can go for Levene test.

For further discussion using R:

Test for normality: Shapiro Wilk test

In order to test the normality of the distribution pattern of a variable, we can use the Shapiro Wilk test. The null hypothesis is that: There is no difference in the distribution of the given data and a normal distribution curve (or in other words the data is normally distributed).
So if the P value is less than 0.05, means that the null hypothesis is rejected or in other words, there is a difference in the distribution of the given data and a normal distribution curve or the given data is not normally distributed.

For this type of data which is not normally distributed, it is time to go for a non parametric test.

Note: Shapiro Wilk can be used to test the normality of residuals in a linear regression model. In R using the epicalc package, it can be done as: shapiro.test(lm(age ~ case.factor)$residuals). In this example, age is the numerical variable and case.factor is the categorical variable as cases and controls and lm stands for linear model.

Monday, June 13, 2011

My comments for the Medical Council of India Vision Document 2015

My comments for the vision document of MCI:

a. The common entrance test, PG entrance exam right at the end of third professional exams and before internship and a licentiate examn at the end of internship are good steps towards removing some of the deficiencies of the current Medical education system. I highly appreciate them.

b. Duration of MBBS course: The long duration of MBBS course and when coupled with PG course/s is a major deterrent for opting for Medical streams as careers nowadays. This issue has been not looked into. If somehow the duration could be reduced even by one year would be a great achievement. The point to ponder is whether 4 1/2 years are really needed ?

c. Change in nomenclature of Diploma courses to Master of Medicine: In my opinion the change in nomenclature is unwarranted as it will create confusion by having two types of Masters degrees in the field of Medicine. I think changing the fundamental structure of Diploma courses is fine but tampering with the name of the course is a futile exercise which can create confusions later on at the field level and also at the institutional levels. 

d. Career opportunities after PG: It is a very good step to think in lines of creating more career opportunities for the medical students. All the career opportunities have been created after PG of two years duration. I think it would be better if career opportunities are created after MBBS course. This would help the students to focus on their careers right from start. e.g. A student wants to enter into hospital administration after completing MBBS should be given the opportunity to rather than that he/she has to wait for two years further to enter into the career of his choice.

This is in response to the comments invited by MCI for improving the medical education standards in the country. The vision document is available online at

Friday, June 3, 2011

Definition of categories of exposure and use of rabies biologicals

These are the WHO recommended definitions of categories of exposure and use of rabies biologicals:

Category III: -single or multiple transdermal bites or scratches, licks on broken skin, contamination of mucous membrane with saliva (i.e. licks) and suspect contacts with bats: use immunoglobulin plus vaccine

Category II: -minor scratches or abrasions without bleeding or and nibbling of uncovered skin: use vaccine alone

Category I : -touching, feeding of animals or licks on intact skin no exposure therefore no prophylaxis if history reliable


Tuesday, May 24, 2011

Facility based care IMNCI (Integrated Management of Neonatal and Childhood Ilnesses))

This facility-based-care IMNCI (Integrated Management of Neonatal and Childhood Illness) training focuses on providing appropriate inpatient management of major causes of neonatal and childhood mortality such as asphyxia, sepsis, and low birth weight in neonates; and pneumonia, diarrhoea, malaria, meningitis, and severe acute malnutrition in children.