what statistical test to use for one sample before and after treatment

by Miss Natalie Beer III Published 2 years ago Updated 2 years ago

Full Answer

Which statistical test should be used to compare treatment groups?

If the frequency of success in two treatment groups is to be compared, Fisher’s exact test is the correct statistical test, particularly with small samples. For large samples (about N> 60), the chi-square test can also be used [Table 1]. Paired samples

Which statistical test is best for unpaired samples?

Unpaired samples: If the frequency of success in two treatment groups is to be compared, Fisher’s exact test is the correct statistical test, particularly with small samples (7). For large samples (about n >60), the chi-square test can also be used (Table).

Which statistical test to interpret medical research articles?

Readers who are acquainted not just with descriptive methods, but also with Pearson’s chi-square test, Fisher’s exact test, and Student’s t test will be able to interpret a large proportion of medical research articles. Criteria are presented for choosing the proper statistical test to be used out of the most frequently applied tests.

What should be considered before performing a statistical test?

Before the data are recorded and the statistical test is selected, the question to be answered and the null hypothesis must be formulated. The test and the level of significance must be specified in the study protocol before the study is performed.

What statistical test do you use for before and after?

Paired ttest – An extremely powerful test for detecting differences (it is, in fact, the most “sensitive” of all our five tests). It is usually used for “Before vs. After” type experiments, where the same individuals are measured before and after the application of some sort of treatment.

How do I know which statistical test to use?

For a statistical test to be valid, your sample size needs to be large enough to approximate the true distribution of the population being studied. To determine which statistical test to use, you need to know: whether your data meets certain assumptions. the types of variables that you're dealing with.

What type of variable is before and after?

For before and after comparison on the same group of people, a paired sample t-test where the dependent variable is continuous (e.g. systolic blood pressure before and after treatment) and McNemar's test where the dependent variable is dichotomous (e.g. hypertension yes / no before and after treatment).

What statistical test can you use to determine if any of the two treatments have a significantly different affect compared to the control?

Paired t-test A paired (samples) t-test is used when you have two related observations (i.e., two observations per subject) and you want to see if the means on these two normally distributed interval variables differ from one another.

When do you use ANOVA or t-test?

The Student's t test is used to compare the means between two groups, whereas ANOVA is used to compare the means among three or more groups.

When do you use chi-square vs t-test?

Both chi-square tests and t tests can test for differences between two groups. However, a t test is used when you have a dependent quantitative variable and an independent categorical variable (with two groups). A chi-square test of independence is used when you have two categorical variables.

What does a chi-square test tell you?

The chi-square test is a hypothesis test designed to test for a statistically significant relationship between nominal and ordinal variables organized in a bivariate table. In other words, it tells us whether two variables are independent of one another.

When do you use independent t-test?

The independent t-test is used when you have two separate groups of individuals or cases in a between-participants design (for example: male vs female; experimental vs control group).

When do we use Pearson correlation?

Pearson's correlation should be used only when there is a linear relationship between variables. It can be a positive or negative relationship, as long as it is significant. Correlation is used for testing in Within Groups studies.

Why we do ANOVA and mean separation?

The overall ANOVA gives no indication of which means are significantly different. If there are only two treatments, there is no problem; but if there are more than two treatments, the problem remains of needing to determine which means are significantly different. This is the process of mean separation.

What is one-way ANOVA and two-way Anova?

A one-way ANOVA only involves one factor or independent variable, whereas there are two independent variables in a two-way ANOVA. 3. In a one-way ANOVA, the one factor or independent variable analyzed has three or more categorical groups. A two-way ANOVA instead compares multiple groups of two factors.

Could you do an ANOVA when there only two treatment conditions?

Although an ANOVA represents a different way of thinking about the significance of differences than a t-test, for a single factor with two treatments there is no advantage to conducting an ANOVA over performing a t-test. In fact, both tests will result in identical P values.

What are the main assumptions of statistical tests?

Statistical tests commonly assume that: the data are normally distributed the groups that are being compared have similar variance the data are i...

What is a test statistic?

A test statistic is a number calculated by a statistical test . It describes how far your observed data is from the null hypothesis of no rela...

What is statistical significance?

Statistical significance is a term used by researchers to state that it is unlikely their observations could have occurred under the null hypothe...

What is the difference between quantitative and categorical variables?

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age). Categorical variables are any variables...

What is the difference between discrete and continuous variables?

Discrete and continuous variables are two types of quantitative variables : Discrete variables represent counts (e.g. the number of objects in a...

What is alternate hypothesis?

alternate hypothesis is a consistent direction of difference. count the number of live and dead patients after treatment with drug or placebo, test the hypothesis that the proportion of live and dead is the same in the two treatments, repeat this experiment at different hospitals. Test. Nominal Variables.

Is the design of a study more important than the analysis?

It is often said that the design of a study is more important than the analysis. A badly designed study can never be retrieved, whereas a poorly analyzed study can usually be re-analyzed.

All Answers (22)

I think a paired t -test might be appropriate here. However, you also should consider your sample size. If the sample size is not big, you might consider to do a nonparametric approach, for example, sign test for paired comparison. This sign test for paired comparison could be done using, for example, R.

Why is it important to select a statistical test before a study begins?

The selection of the statistical test before the study begins ensures that the study results do not influence the test selection. The decision for a statistical test is based on the scientific question to be answered, the data structure and the study design.

What is statistical testing?

Statistical tests are mathematical tools for analyzing quantitative data generated in a research study. The multitude of statistical tests makes a researcher difficult to remember which statistical test to use in which condition. There are various points which one needs to ponder upon while choosing a statistical test.

Why are ratio and interval measured as continuous?

Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically, sometimes they are grouped together as categorical variables, whereas ratio and interval measurements are grouped together as quantitative or continuous variables due to their numerical nature.

Is there a hypothesis in a prevalence study?

In some cases there is no hypothesis; the investigator just wants to “see what is there”. For example, in a prevalence study, there is no hypothesis to test , and the size of the study is determined by how accurately the investigator wants to determine the prevalence.

All Answers (2)

You should use a mixed model to analyse these data. Mixed models let you specify a random effect, in your case the different subjects. The model will "understand" that each subject represents a cohesive block of measures, and should help you with the differences between them.

Why subtract pre values from post values?

Lots of people do this. However, the purpose of subtracting the pre values from the post values is to control for variation in the pre values. Put another way, if the pre values were all the same, you could just use the post values, which would fully reflect the difference.

Can you do a MANOVA if you have a paired t-test?

You can do a MANOVA to control for the fact that a and b might be correlated. If a and b are not correlated, you could also probably make the case for doing two paired t-tests, one for a and one for b. People do this all the time, even if a and b are indeed correlated.

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