MEDICAL STATISTICS BOOKS PDF

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procedures, rather than learn a set of “cook-book recipes.” In many statistics books aimed at medical students or biomedical researchers, the. Medical Statistics. Fourth Edition. A Textbook for the Health Sciences. David Machin. Division of Clinical Trials and Epidemiological Sciences, National Cancer. To enhance focus, this book is titled Medical Biostatistics. to demonstrate that biostatistics is not just statistics applied to medicine and health.


Medical Statistics Books Pdf

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This book is intended to be an introduction to medical statistics but one which mean with a calculator), and so most statistics books were full of equations and. Results 1 - 10 Medical Statistics Made Easy. Pages·· Oxford Handbook of Medical Statistics Pdfdrive:hope Give books away. Get books you. Medical Statistics Made Easy. Pages DOVER BOOKS ON ART INSTRUCTION. David Evans†, Paul Gruba, Justin Zobel · Download PDF Chapter.

Actions Shares. Embeds 0 No embeds. No notes for slide. Book details Author: Martin Bland Pages: Oup Oxford Language: English ISBN Description this book Now in its Fourth Edition, An Introduction to Medical Statistics continues to be a must- have textbook for anyone who needs a clear logical guide to the subject.

Click Here To Download https: If you want to download this book, click link in the last page 5. You just clipped your first slide! Clipping is a handy way to collect important slides you want to go back to later. Now customize the name of a clipboard to store your clips. Visibility Others can see my Clipboard. Cancel Save. The distribution should be normal. We need not bother about difficult calcu- lations. We can do it easily using Excel program as I explained earlier. This table shows the time since pain to surgery in perforated and non-perforated appendicitis.

So chi test or Fisher test cannot be used. The data are continuous variables mean- ing. Click calculate exact chi2. This is used to calculate the probability of two normal distribution curves being the same or different. Select the significance level here 0. The P value is 1. We need two sets of data to compare.

Compare t value with the table. Then the whole exer- cise of the study has gone waste. Otherwise one may argue that the results are due to different age pattern of the group. In case of control studies. It is essential to prove that there is no statistically significant difference in the age distribution between the two groups.

Standard deviation for the Table 5. How to do it? For simplicity. This is the web site of Social Science Statistics [http: We can have more number. Data entered in the boxes provided. Two tailed test selected.

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Significance level selected as 0. So there is no significant difference in the age distribution between the groups.

If data falling on both sides to be considered. One tailed test Two tailed test. Result is shown in red fonts We have the result: It is obvious that repair with intraperitoneal mesh cannot produce fewer adhesions than repair without mesh.

Paired T Tests 49 One-tailed test: The curve tails of the curve are taken. Stapled hemorrhoidectomy is better than conventional hemorrhoidectomy. Example 2 In comparing intraperitoneal mesh repair and nonmesh repair with respect to intra-abdominal adhesion formation. In the study. To apply paired T test. So use a two-tailed test. For each patient. Conventional hemorrhoidectomy is better than stapled hemorrhoidectomy. An example for this is preoperative and postoperative weights after weight-reducing surgery.

So use a one- tailed test. The area area represents 0. Other conditions of T test are the same. Paired T Tests Paired T tests are used when there are two sets of observations for each subject. Another example is to study the effectivity of lateral pancreaticojejunostomy in relieving pain in chronic pancreatitis. To calculate the paired T test. In the box for the number of items. The explanation is also avail- able on the same page http: Anova 51 In the boxes A01 to B You need to understand certain terminologies for using this which test to use?

Which Test to Use? A beginner often finds it difficult to decide which test is to be used for the data under consideration. Web sites have solutions to this also. Once we understand our data, if necessary by clicking on explanation, we have to select the proper option and click NEXT. It takes to the next step, and after a few questions about the data, the wizard suggests the best test for our data. For example, we shall see which test to be used for the data of Table 5.

Once we select the options, the wizard suggested chi test. It also suggested alternative tests, Fisher exact test, and Z test for two population propor- tions Figs.

One of the prerequisites for using T test is that the data should follow a normal dis- tribution curve. If the data follow a skewed distribution curve nonparametric , Mann—Whitney test can be used for an explanation on normal distribution curve and skewed distribution curve, see Chap.

It can be used if certain conditions are satisfied:. Two samples should be drawn from the same population. Data are independent. Data are ordinal for Rank Test can be ranked higher or lower. Blood sugar levels and can be ranked: The data are ordinal.

If the difference between the consecutive observations is not assumed to be equal, T test cannot be used. MWW test can be used. Under this condi- tion the data follows skewed distribution or nonparametric distribution curve. The data are following a skewed distribution curve or. Anova 55 Example The age distribution of the study group and control group of patients undergoing mesh hernioplasty and herniorrhaphy without mesh is shown in Table 5.

Is the incidence of headache related to the size of the needle used? In a hospital patients undergoing elective lower abdominal surgery were randomly assigned to two groups. T test. It is important for every clinician to understand what the tests of significance are and why these tests should be applied. Examples and Self-Tests: All Fiction Examples Question 1 Subarachnoid block using spinal needles to inject drug into the subarachnoid space is practiced in lower abdominal surgeries.

The Internet. There are many other tests. Postoperatively many patients complain of headache spinal headache. If we know the basics. How to do the test is comparatively easy. Others advocate fixing the mesh. A researcher designed a study to evalu- ate if one method is superior to the other. In group B 26 G needle was used. In the first group. Question 2 In laparoscopic hernioplasty.

Their operative statistics show the recurrent laryngeal nerve injury rates as shown in the table Table 5. He randomly assigned patients to three groups. In the second group of patients. Fixation may be done with mechanical devices like tackers or with glue.

Questions and Tasks a Present the data in the form of a table. The results were tabulated Table 5. Other details of the procedure. Recurrence was assessed after 2 years of follow-up. Many argue that fixation of mesh is unnecessary. Summary 57 Intervention: In group A. The results showed that out of patients in group A 22 patients developed postspinal headache. In the third group of patients. How you would do it? What is the degree of freedom for this table?

Question 3 Two surgeons surgeon A and surgeon B are experts in thyroidectomy working in a hospital doing a large number of thyroidectomies. In group B.

N injuries Percentage Surgeon A 2 1. He measured the area of the ulcers and assigned the patients randomly into study group and control group. For study group patients. In order to test the claim. All patients did not have any factors delaying the healing like diabetes mellitus. The derma- tologist assumes that the data is parametric Tables 5. Is it so? How do you decide based on the data furnished? Which test do you use and why?

Question 4 Local application of a drug X gel in the form of a gel is claimed by the company that it helps in faster healing of the ulcer. For control group patients. After 2 weeks he measured the area of the ulcers and tabulated the results. He chose patients with healthy posttrau- matic ulcers without infection with a size of 4—5 cm.

What type of variables you are dealing with? What type of study is this?

How will you ensure the groups of patients are comparable? Which test would you do to see if the claim of X gel is valid? If there were to be no control group, how do you test? How do you interpret the results? Is it correct to apply paired T test? Question 5 If the data were to be nonparametric, how will you proceed to test the claim?

Question 1 The table for the data is given in Table 5. These are categorical variables. Outcome data can fall in only one of the two categories: Chi test can be applied. The P value is 0. There is no significant difference in the incidence of postspinal headache whether 24 G or 26 G spinal needle was used.

Question 2 Chi test can be applied for this data also. As P value is 0. In other words, there is no significant difference in the competence of the two surgeons.

Question 4 The data shows continuous variable, since the area can take any number of values. It is a randomized control trial. To ensure that the two groups are comparable, we have to compare the initial area of the ulcers of the two groups and find the P value.

Initial size of the ulcer in control group Control group Initial area Patient 1 Summary 63 By applying T test for this data. The der- matologist concludes by saying X gel does not hasten the healing of the ulcers under the said conditions.

To see the efficacy claim of X gel. Decrease in the size of the ulcer in the Control group Decrease in size control group Patient 1 8. But T test showed result is not significant.

In the text data. Paired T test using internet based calculator P is 0: In the present data. So whatever the results we got should be due to the drug.

Observe the difference between the data presented in the main text to explain paired T test and the present data. That is the importance of control study. If paired T test is applied for the data of control group similarly.

If the phar- maceutical company shows the results of the study group alone and claims the drug is useful.

This is because of the natural healing process of the ulcers. Summary 65 If there were to be no control group. The data is assumed to be parametric. How to explain these seemingly con- tradictory results? We have to understand that ulcers can heal by natural process. There are two sets of data for each patient. The probability of a null hypothesis being true is 0.

As explained in the main text. Question 5 If the data were to be nonparametric. T test can be used. T test can be applied to each pair of groups individually. If there are only two groups. If there are multiple groups. ANOVA is a combination of many concepts and is used in several settings. Although it tests the difference in the means.

This increase can have deleterious effects on the cardiovascular system. Some basic concepts are explained here. T test is used when comparing two groups.

Drug A and Drug B. Two drugs. Patients undergoing endotracheal intuba- tions were randomly divided into three groups. BP was recorded at 5 min of endotracheal intubation. An investigator wanted to test the beneficial effects of these drugs.

Actual calculation is complicated and beyond imagination of the beginner. Drug A group. Drug B group.

If T test is to be applied. In fact. Table 6.

Suffice it to say. If there are four variables. ANOVA is used when three or more groups are to be compared. Example 1 There will be an increase in systolic blood pressure during endotracheal intubation.

The increase in blood pressure the difference between BP prior to endotracheal intuba- tion and at 5 min of endotracheal intubation was tabulated. When multiple tests are used. Rank Test: Wilcoxon Signed-Rank Test 69 For this type of data. Handbook of Biological Statistics 3rd ed.

Ronald Fisher. Example 2 In patients with chronic pain. Visual analog score is recorded again after 2 h. The results are given in the table. It is a paired test and is used as an alternative to paired T test when data are nonparametric. Worked examples can be read on http: Wilcoxon signed-rank test is to be used in this type of data. ANOVA is appropriate. Drugs are tested on the same 14 patients.

Each drug is given on different day when no other analgesics are used. Sparky House Publishing. There were reasons to believe that data are nonparametric. Did You Know This? The term variance was introduced by an evolutionary biologist. Wilcoxon Signed-Rank Test In very simple words. But five times when compared with hernioplasty group.

If the risk ratio is 1. There is no significant difference in the effi- cacy of these two drugs. Risk ratio is calculated when two groups are compared. This means the patients who undergo herniorrha- phy without mesh are at fivefolds higher risk than patients who undergo hernio- plasty with mesh. This example is also useful to highlight why we should know how to interpret the data and statistical terms.

If we analyze the actual data and not the conclusion. Two recurrences mean 98 no recurrences. If we do not know the proper interpretation. Reduced mortality is divided by the mortality: Suppose there is a condition which has a mortality of 3 in Odds Ratio It is the ratio of odds of the study group to odds of the control group.

ARR is the reduced mortality divided by the total number of patients: Relation Between Two Factors If two parameters have a linear relationship. Sometimes the pharmaceutical companies use the term relative risk reduction. The relationship may be positive or negative.

Then odds ratio is odds of mortality of the study group divided by the mortality of odds of the control group. The second parameter may or may not be the cause for the first or vice versa. Negative Correlation Fig. But it does not mean the second variable always exists whenever the first variable is present. As the negative lapa- rotomy rate increases in a series. The correlation indicates only a relationship: Lower body mass index BMI associated with lower death from cardiac arrest is another example for positive correlation.

If negative laparotomy rate and perforation rate data are collected from different series of study on acute appendicitis and plot- ted as graph. Positive Correlation Fig. So perforation rate and negative laparotomy are said to be having a negative correla- tion Fig. There may be nonlinear correlation where correlation coefficient is small indi- cating a weak relationship but association may be strong. If there is no relation at all.

If the sample size is large. Regression 73 Think over it: Consider smoking and the incidence of lung cancer as two variables. It is important to clarify the difference between correlation and regression. If the correlation coefficient value is nearer to 0.

If there is a perfect relationship. Correlation is not an all-or-none phenomenon. If the correlation coeffi- cient value is away from 0. There may be multiple factors correlating with a variable.

Depending upon the strength of relationship. Regression quan- tifies the relationship. They are not revealed because association is not linear. The significance of correlation also depends upon the sample size. Do they correlate? If so what type? Correlation Coefficient r Correlation coefficient measures the strength of relationship.

Correlation only indicates the strength of the relationship between two factors or parameters. Regression The idea is similar to and sometimes confused with correlation. It can quantify the relation: If the correlation coefficient value is away from 0. Regression is used only when there is cause—effect relation- ship. Each dot represents a pair of data. When a number of data are entered.

When two dependent data are plotted as graph. If one of the parameters is known. Weight is marked on x-axis horizontal of the graph and height is marked in y-axis vertical. Regression 75 If a straight line which can best fit all the data is drawn. Weight kg vs height cm Similarly if height is known. The slope is the regression co-efficient.

Weight kg vs height cm If one of the parameter is known. The slope represents regression coefficient Fig. From the graph.

Epidemiology and Medical Statistics, Volume 27

Interpretation of the results of multiple regression is complex and difficult as multiple variables are involved and different variables may have different degrees of influence. It is important to restrict calculations within the data range. Other Types of Regressions Logistic Regression It is a statistical method of analyzing variables one or more to predict whether an outcome falls into a category or not.

Dependent variable is categorical. Observational data is presented in Table 6. Calculations should not be extended beyond the range. Logistic regression applicable Age group Average no. Multiple Regression: To Predict an Outcome Multiple regression is similar to linear regression. Here the outcome dependent vari- able or target variable is predicted depending upon two more input variables. Other Types of Regressions 77 on the outcome.

That means ten new cases of cleft lip are detected in a year. The average rate is known. If a new case of cleft lip is detected today. With these data. The next case may be detected on the same day. So both the conditions mentioned above are satisfied: Poisson regres- sion is applicable. Regression quantifies the relationship. Predicting the 5-year survival rate is the outcome. Correlation indicates only the relationship between two variables.

Example 3 Let us assume that cleft lip incidence is 10 per year in a particular city. Cox regression aims to estimate the hazard ratio. HR of death from lung cancer is 2 for smokers means the chances of an individual dying from lung cancer is twice if he is a smoker compared to nonsmoker.

Regression indicates cause—effect relationship. T status. Hazard ratio HR is the ratio something outcome happening in one group to that of another group. Correlation gives strength of the relation- ship. Cox Regression Cox regression is used for survival analysis. Events are independent of the time since the last event.

It calculates the time to certain event. With regression. Based on HR. N status.

It can be seen on the graph Fig. So it appears the data is incomplete and cannot be presented. Similar plot can be constructed for other events also. However the data can be presented as survival analysis Fig.

Here recurrence is taken as the event instead of death. It is useful when different patients are followed up for different periods of time. We do not have data of all patients regarding mortality. It means that at 4 years patients with stage 2 disease are 1.

Kaplan—Meier estimator has a number of steps. Control group patients received a pla- cebo. Multivariate Analysis There may be multiple factors affecting the outcome. The line has several small steps. At the end of the study. It plots the percentage of survivors against time.

Each point on the graph line has a corresponding point on y-axis showing the num- ber or percentage of survivors and on x-axis showing the time in months or years.

For this type of data Kaplan—Meier estimator or survival graph can be used. Then we have to quantify each of them in the order of importance. Study group patients received the Drug X. At each step the proportion of survivors is plotted against time. A number of similar graphs can be found on the web site.

Medical Statistics

The dates are recorded when a patient enters the study or lost for follow-up or excluded from the study or dies. When death occurs it is recorded with date. In a city positive patients are found and are randomly assigned to study group and control group. Interpretation and understanding the interpretation is more difficult. On the con side. Multivariate analysis is more realistic in a variety of medical conditions.

It can be used for more complex data where univariate analysis is not possible. Examples where multivariate analysis is applicable Example 5 To study the factors affecting weight reduction. A few examples can help to understand the ideas behind the analysis and when it can be applied.

If univariate analysis is done. The aim of multivariate analysis is to predict the outcome based on some existing informa- tion. Multivariate analysis is not a single test. A factor can have many variables. How do these data affect outcome weight reduction after an intervention? Example 6 The risk of stroke and cardiac event is dependent upon many factors like hypercho- lesterolemia.

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Planning Studies 1. Planning Analysis 2. Probability and Relative Frequency 3. Distributions 4. Descriptive Statistics 5. Finding Probabilities 6. Confidence Intervals 7. Hypothesis Testing 8.

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Tests on Categorical Data 9. Risks and Odds Tests on Ranked Data Basics The Signed-Rank Test Description this book Now in its Fourth Edition, An Introduction to Medical Statistics continues to be a must- have textbook for anyone who needs a clear logical guide to the subject.

They had a lot of materials but were unable to convert it into an article or a research paper. Written by three experts with wide teaching and consulting experience, Medical Statistics: Find the mean of these squared deviations variance. Observe the question: Then only we accept the results that there is differ- ence between the groups.

Correlation gives strength of the relation- ship. He got many best paper awards in the conferences. The data are ordinal. By applying tests of significance.