| Statistical test | Description |
|---|---|
| Student's t-test | Test for continuous data. Investigates whether the expected values for two groups are the same, assuming that the data are normally distributed. The test can be used for paired or unpaired groups |
What are the types of statistical tests?
1. Standard ttest – The most basic type of statistical test, for use when you are comparing the means from exactly TWO Groups, such as the Control Group versus the Experimental Group.
What type of t-test should I use for the treatment group?
Normally I would just use a paired t-test for the 'treatment' group to see if the difference (increase) is significant, since I took repeated measure from the same subject (i.e. pre and post test).
What are the types of control groups used in research?
Although control groups are more common in experimental research, they can be used in other types of research too. Researchers generally rely on non-experimental control groups in two cases: quasi-experimental or matching design.
What statistical test should I use in my lab or field study?
All you have to do is pick the right test for your particular lab experiment or field study. The statistical test that you select will depend upon your experimental design, especially the sorts of Groups (Control and/or Experimental), Variables (Independent and Response), and Treatment Levels that you are working with.
What kind of statistical test should I use to compare two groups?
The two most widely used statistical techniques for comparing two groups, where the measurements of the groups are normally distributed, are the Independent Group t-test and the Paired t-test.
Which type of test do you use when you have two different groups of participants to compare against one another?
The dependent t-test (also called the paired t-test or paired-samples t-test) compares the means of two related groups to determine whether there is a statistically significant difference between these means.
What type of statistical test is used to test an effect when more than 2 groups or conditions are being considered?
Analysis of variance (ANOVA) is used to test an effect when more than two groups or conditions are being considered. The average variance is used in the calculation of mean differences and sampling error, which is why the test is called analysis of variance.
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.
Can you use ANOVA for 2 groups?
Typically, a one-way ANOVA is used when you have three or more categorical, independent groups, but it can be used for just two groups (but an independent-samples t-test is more commonly used for two groups).
Which statistical test would we use when we collected two measures from the same group of participants?
If I've described your experimental scenario accurately, the most common test used for this is a two-way repeated measures ANOVA.
What is a ANOVA test used for?
The ANOVA test allows a comparison of more than two groups at the same time to determine whether a relationship exists between them.
When would you use a two tailed test?
A two-tailed test is appropriate if you want to determine if there is any difference between the groups you are comparing. For instance, if you want to see if Group A scored higher or lower than Group B, then you would want to use a two-tailed test.
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.
What statistical treatment is used to check if the means of two or more groups are significantly different from each other?
t-testA t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. The t-test is one of many tests used for the purpose of hypothesis testing in statistics. Calculating a t-test requires three key data values.
What statistic would you use to test whether the means of a two group experiment were significantly different?
ANOVA (Analysis of Variance) is a statistical test used to analyze the difference between the means of more than two groups. A two-way ANOVA is used to estimate how the mean of a quantitative variable changes according to the levels of two categorical variables.
Can you do at test with more than 2 groups?
Motivation. A t-test is useful to find out whether there is a significant difference between two groups. However, a t-test cannot be used to compare between three or more independent groups.
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 a control group in science?
Revised on April 19, 2021. In a scientific study, a control group is used to establish a cause-and-effect relationship by isolating the effect of an independent variable. Researchers change the independent variable in the treatment group ...
What does it mean to use a control group?
Then they compare the results of these groups. Using a control group means that any change in the dependent variable can be attributed to the independent variable.
How to ensure that all potential confounding variables are accounted for?
Ensure that all potential confounding variables are accounted for, preferably through an experimental design if possible, since it is difficult to control for all the possible confounders outside of an experimental environment.
How to minimize confounding variables?
Randomly assign your subjects into control and treatment groups. This method will allow you to not only minimize the differences between the two groups on confounding variables that you can directly observe, but also those you cannot.
How to test the effectiveness of a pill?
To test its effectiveness, you run an experiment with a treatment and two control groups. The treatment group gets the new pill. Control group 1 gets an identical-looking sugar pill (a placebo) Control group 2 gets a pill already approved to treat high blood pressure. Since the only variable that differs between the three groups is the type ...
What is treatment in research?
The treatment is any independent variable manipulated by the experimenters, and its exact form depends on the type of research being performed. In a medical trial, it might be a new drug or therapy. In public policy studies, it could be a new social policy that some receive and not others.
What is the treatment group?
The treatment group (also called the experimental group) receives the treatment whose effect the researcher is interested in. The control group receives either no treatment, a standard treatment whose effect is already known, or a placebo (a fake treatment). The treatment is any independent variable manipulated by the experimenters, ...
Which test is used for analysis of two groups?
T-test is used for the analysis of two groups and ANOVA is used for more than two groups. Is that right?
What is an alternate design for the groups comparison?
An alternate design for the groups comparison would be one-way ancova ; such that randomly occurring differences between groups at baseline would be controlled for, and the group/condition comparison would be on post scores adjusted for pre/baseline differences.
What does paired t-test tell you?
Paired t-test will tell you if training is effective or not. You need to compare the data after training with the control group using unpaired t test. If more than two groups you can use ANOVA.
Why do you conduct Levene's test?
I also recommend conducting Levene's test to determine if the groups have similar error variances. This will give you at least some confidence that the groups are similar.
Does Mauchley's test apply to repeated measures?
For repeated measures factors, Mauchley's test is applicable only if there are more than two measurements/levels of the factor. You have two (pre, post), so it does not apply.
Is repeated measures ANOVA better than t-tests?
Yes, a repeated-measures ANOVA is better than conducting multiple t-tests since you increase the risk of committing a Type-I error with each test. In this case, a repeated-measures ANOVA including 'training' as a between-subjects factor with two levels (training, control) and 'time' as a within-subjects factor with two levels (pre, post).
Is T1 a zero time?
I assume that t1 can be encoded as zero time, i.e., there is no treatment or training effect at this time point (i.e., these are "baseline measurements"). Thus:
Is the practice effect significant?
As you see, the model would tell you that your "practice effect" (slope time1) is not significant but the treatment has a highly significant effect on the slope. I believe this is what you want to know. (The random intercept variance is very small because there is no random slope although one is needed.
Is slope time1 significant?
As you see, the model would tell you that your "practice effect" (slope time1) is not significant but the treatment has a highly significant effect on the slope. I believe this is what you want to know.
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How to report percentage change?
Afterwise you can report percentage change by dividing the (mean post-value of the group adjusted for the pre-values - mean pre-value of the group)/ (mean pre-value of the group)*100. In that way you can compare the percentage change between groups.
Do you need to do a separate t-test?
Consider repeated measures ANCOVA or repeated measures ANOVA. You would also not need to do separate t-tests because you could simply analyze the main effects of the ANOVA or ANCOVA to examine the effect of the intervention. Either way, you would want to use repeated ...
What is the endpoint of a statistical test?
The outcome variable (endpoint) is defined at the same time the question to be answered is formulated . Two criteria are decisive for the selection of the statistical test:
What is continuous data test?
Test for continuous data. Investigates whether the expected values for two groups are the same, assuming that the data are normally distributed. The test can be used for paired or unpaired groups.
What is an unpaired independent study design?
With an unpaired or independent study design, results for each patient are only available under a single set of conditions. The results of two (or more) groups are then compared. There may be differences in the sizes of the groups.
What is a 2 x 2 table?
Suitable for binary data in unpaired samples: the 2 x 2 table is used to compare treatment effects or the frequencies of side effects in two treatment groups
How to decide if a test is one tailed or two tailed?
The decision for a statistical test is based on the scientific question to be answered, the data structure , and the study design. 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. It must be decided whether the test should be one-tailed or two-tailed. If the test is two-tailed, this means that the direction of the expected difference is unclear. One does not know whether there is a difference between the new drug and placebo with respect to efficacy. It is unclear in which direction the difference may be. (The new drug might even work less well than the placebo). A one-tailed test should only be performed when there is clear evidence that the intervention should only act in one direction.
Which statistic leads to retention of the null hypothesis?
p≥0.05 leads to retention of the null hypothesis
Is there a difference between the active treatment and the placebo?
The null hypothesis is then: “There is no difference between the active treatment and the placebo with respect to antihypertensive activity” (effect = 0).
What test to use for residuals?
If you are not comfortable with your plots of residuals, you can use Kruskal-Wallis test.
Why is ANOVA used in a study?
In all publications Anova or T test is used to compare cell viability between treatment and control groups. But usually only 3 independent experiments are done and this small sample cannot have normal distribution. Shouldn't the authors use nonparametric tests in this case? Or maybe all the replicates from one experiment are included in the analysis, not only the mean value of the experiment?
How to test assumptions of anova?
To test the assumptions of anova, you want to plot the residuals from the whole model as a histogram or qq plot. The residuals should be fairly normally distributed. You also want to plot the residuals vs. the predicted values (or something similar) to check for homoscedasticity.
What is the assumption of normal distribution?
The assumption of "normal distribution" requires that your sample (s) was/were drawn from a "normally distributed" population. It does not mean that the sample itself must be "normally distributed". Therefore your statement "...and this small sample cannot have normal distribution" is not appropriate and makes no sense.
Is ANOVA more appropriate for continuous drug concentration?
I totally agree that other methods than ANOVA are more appropriate if drug concentration is needed to be treated as continuous. But according to her description, she just wants to find an association. So a simple ANOVA or KW seem to suffice.
Is Y viability or concentration?
Yes Y is the viability and C is the concentration.
Is concentration a continuous variable?
In this case, Concentration could be treated as either a continuous or a nominal variable.
Control Groups in Experiments
- Control groups are essential to experimental design. When researchers are interested in the impact of a new treatment, they randomly divide their study participants into at least two groups: 1. The treatment group (also called the experimental group) receives the treatment whose effect the researcher is interested in. 2. The control groupreceives e...
Control Groups in Non-Experimental Research
- Although control groups are more common in experimental research, they can be used in other types of research too. Researchers generally rely on non-experimental control groups in two cases: quasi-experimental or matching design.
Importance of Control Groups
- Control groups help ensure the internal validityof your research. You might see a difference over time in your dependent variable in your treatment group. However, without a control group, it is difficult to know whether the change has arisen from the treatment. It is possible that the change is due to some other variables. If you use a control group that is identical in every other way to t…