if treatment is not independent which analysis method should i use

What analytical methods should I use in my questionnaire?

Hello, using different analytical methods depends on what your research is aimed at and your data. Questionnaires are often advised to start with the reliability testing of all relevant items (e.g. Cronbach alpha measure of internal consistency). Grimm, L.G., & Yarnold, P.R. (Eds.).

Is it easy for a non-statistical person to do data analysis?

I think it is very easy for those of us familiar with statistics to answer questions in that language, but for the non-statistical person, that gives them very little to work with. The reality of data analysis starts with the simple reality of "what was the question and what did your respondents answer?"

How to choose a data analysis method?

How to Choose a Data Analysis Method. Which data analysis method you choose will depend greatly on the dataset you are dealing with and what you intend to achieve with it. If your dataset consists of quantitative data, you’ll have to use a quantitative method; if your dataset consists of qualitative data, you’ll have to use a qualitative method.

When to use parametric and nonparametric methods in data analysis?

It is recommended that when sample size is small, only on highly normally distributed data, parametric method should be used otherwise corresponding nonparametric methods should be preferred.

What type of model would you use if you wanted to find the relationship between dependent and independent variables?

Use linear regression to understand the mean change in a dependent variable given a one-unit change in each independent variable. You can also use polynomials to model curvature and include interaction effects.

What type of test do you use when your dependent and independent variable are both categorical?

If the dependent variable is normally distributed and you have a categorical independent variable is paired then you use a PAIRED T TEST. However, If the dependent variable is not normally distributed and you have a categorical independent variable is paired then you use WILCOXON SIGN RANK TEST.

How do you choose a statistical analysis method?

Selection of appropriate statistical method depends on the following three things: Aim and objective of the study, Type and distribution of the data used, and Nature of the observations (paired/unpaired).

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 is chi-square test used for?

A chi-square test is a statistical test used to compare observed results with expected results. The purpose of this test is to determine if a difference between observed data and expected data is due to chance, or if it is due to a relationship between the variables you are studying.

Can I use ANOVA for categorical dependent variable?

A one-way analysis of variance (ANOVA) is used when you have a categorical independent variable (with two or more categories) and a normally distributed interval dependent variable and you wish to test for differences in the means of the dependent variable broken down by the levels of the independent variable.

What is the best data analysis method?

Two main qualitative data analysis techniques used by data analysts are content analysis and discourse analysis. Another popular method is narrative analysis, which focuses on stories and experiences shared by a study's participants.

What are the reason of using parametric test?

Typically, a parametric test is preferred because it has better ability to distinguish between the two arms. In other words, it is better at highlighting the weirdness of the distribution. Nonparametric tests are about 95% as powerful as parametric tests. However, nonparametric tests are often necessary.

What are the 5 basic methods of statistical analysis?

It all comes down to using the right methods for statistical analysis, which is how we process and collect samples of data to uncover patterns and trends. For this analysis, there are five to choose from: mean, standard deviation, regression, hypothesis testing, and sample size determination.

What does a multivariate analysis show?

Multivariate analysis of variance (MANOVA) is used to measure the effect of multiple independent variables on two or more dependent variables. With MANOVA, it's important to note that the independent variables are categorical, while the dependent variables are metric in nature.

What is the best statistical test 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.

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...

How many independent variables are required to predict outcome variables?

Predict one outcome variable by at least one independent variable

What are the two main statistical methods used in data analysis?

Two main statistical methods are used in data analysis: descriptive statistics, which summarizes data using indexes such as mean and median and another is inferential statistics, which draw conclusions from data using statistical tests such as student's t-test.

What is the statistical method used to compare the proportions between two groups?

The statistical methods used to compare the proportions are considered nonparametric methods and these methods have no alternative parametric methods. Pearson Chi-square test and Fisher exact test is used to compare the proportions between two or more independent groups. To test the change in proportions between two paired groups, McNemar test is used while Cochran Q test is used for the same objective among three or more paired groups. Z test for proportions is used to compare the proportions between two groups for independent as well as dependent groups.[6,7,8] [Table 2].

What are the two types of statistical methods?

Inferential statistical methods fall into two possible categorizations: parametric and nonparametric. All type of statistical methods those are used to compare the means are called parametric while statistical methods used to compare other than means (ex-median/mean ranks/proportions) are called nonparametric methods.

What are the three things that determine the selection of a statistical method?

Selection of appropriate statistical method depends on the following three things: Aim and objective of the study , Type and distribution of the data used , and Nature of the observations (paired/unpaired).

What is statistical method?

In statistics, for each specific situation, statistical methods are available to analysis and interpretation of the data. To select the appropriate statistical method, one need to know the assumption and conditions of the statistical methods, so that proper statistical method can be selected for data analysis.[1] .

What is statistical method in biostatistics?

In biostatistics, for each of the specific situation, statistical methods are available for analysis and interpretation of the data. To select the appropriate statistical method, one need to know the assumption and conditions of the statistical methods, so that proper statistical method can be selected for data analysis.

Why are non-parametric tests useful?

Non-parametric tests don’t make as many assumptions about the data , and are useful when one or more of the common statistical assumptions are violated. However, the inferences they make aren’t as strong as with parametric tests.

What happens if you don't meet the assumption of independence of observations?

If your data do not meet the assumption of independence of observations, you may be able to use a test that accounts for structure in your data (repeated-measures tests or tests that include blocking variables).

What happens if the test statistic is less extreme than the one calculated from the null hypothesis?

If the value of the test statistic is less extreme than the one calculated from the null hypothesis, then you can infer no statistically significant relationship between the predictor and outcome variables.

What is statistical test?

They can be used to: determine whether a predictor variable has a statistically significant relationship with an outcome variable. estimate the difference between two or more groups. Statistical tests assume a null hypothesis of no relationship or no difference between groups.

How does a statistical test work?

Statistical tests work by calculating a test statistic – a number that describes how much the relationship between variables in your test differs from the null hypothesis of no relationship.

What happens if you don't meet the assumptions of normality or homogeneity of variance?

If your data do not meet the assumptions of normality or homogeneity of variance, you may be able to perform a nonparametric statistical test, which allows you to make comparisons without any assumptions about the data distribution.

What do you need to know to determine which statistical test to use?

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.

Which method is used to explain or predict data?

Hypothesis testing is the perhaps the most interesting method, since it allows you to find relationships, which can then be used to explain or predict data. As for qualitative data analysis methods, content analysis is the primary approach to describing textual data, while grounded theory can be used to explain or predict any qualitative data.

What is data analysis?

Data analysis methods are specific tools or techniques you can use to analyze data. They come in two broad categories, depending on whether the data is quantitative or qualitative. Quantitative data is data that can be expressed in numbers. As a result, a big part of quantitative data analysis is using statistical methods to find objective patterns ...

Why is data analysis important?

Data analysis enables you to get the most out of data. Not only does it allow you to describe past events, but it also allows you to explain them, find relationships between them, and predict them. An essential part of data analysis is using the right data analysis methods. Depending on whether your data analysis revolves around quantitative and/or ...

Why do we use averages?

In particular, using averages allows you to smooth out datasets and draw more accurate conclusions; without averages, you might find yourself comparing data to an unusually low or high number.

What are the three types of averages?

In fact, there are three well-established types of average: the mean, median, and mode. The mean is what most people think of when you say the word average. It’s calculated by summing up the values in a dataset, and dividing the result by the number of values. The median is the middle number in the list.

Why do we use correlation test?

Usually, it’s used to confirm the relationship between two variables, to a certain level of confidence . This is also a very popular method in the real world, especially in academia, since it’s essential to assess whether or not correlations are random.

Is content analysis qualitative or quantitative?

Since content is mostly qualitative data, statistical methods are less appropriate. Instead, the content must be analyzed by an individual, who will provide a subjective opinion on its meaning, tone, or other characteristics. As an example of content analysis, consider a person reading a letter. How they interpret the letter might be different ...

What data analysis to use?

What data analysis to use also depending on your conceptual framework / research model and their hypotheses. Once you have decided the data analysis, you can choose the relevant statistical software. Generally on the surface you can use data analyses like normality test (deciding to use parametric / non-parametric statistics), descriptive statistics, reliability test (Cronbach Alpha / Composite Reliability), Pearson / Spearman correlational test etc.

What software do you use for non correlational research?

whereby you can use software like SPSS, R, SAS etc.

How to collect primary data using a questionnaire?

As you are going to collect primary data using a questionnaire, it is preferable to start with testing the questionnaire using reliability test. Then start analysis by describing your sample. If your data are quantitative, do normality test, if the distribution is normal use the mean as a measure of central tendency and the standard deviation as a measure of dispersion. Use Parametric Methods for testing hypotheses and estimation, Person coefficient as a measurement of correlation between variables.

How to find the minimum and maximum of a Likert scale?

To determine the minimum and the maximum length of the 5-point Likert type scale, the range is calculated by (5 − 1 = 4) then divided by five as it is the greatest value of the scale (4 ÷ 5 = 0.80). Afterwards, number one which is the least value in the scale was added in order to identify the maximum of this cell. The length of the cells is determined below:

What does it look like based on information you'd provided?

Based on information you'd provided, looks like is a correlational research.

What is the main point of a statistical analysis?

The key point is your outcome and also the type of your outcome (numeric, binary, count, proportion, etc) .

Is the advice given already excellent?

The advice given already is excellent and clearly given by individuals with a greater knowledge of statistics than I have. The uncertainty of what the research proposal is for and the research design makes this a very difficult question to answer, as noted by some of the other respondents to your request.

Is it OK to use an approximate model?

My view is that the models we use are always approximations and sometimes it is OK to go with an approximate model that has good properties in the current situation (e.g., a t test for rating scale data). However, this requires awareness of the limitations of the model and the willingness to check assumptions.

Is a two tailed t-test a good tool?

I have a similar research done in print vs online journalism. Two tailed T-test is a good tool to find if there is significant difference between the groups. If you consequently want to determine if the difference (if there is such) is related to time spent online, specifically, there is a correlation analysis (Pierson's correlation) you might want to try. Good luck with your research!

Is the Likert scale an interval scale?

Chi square, as suggested. Often the Likert scale is even used as an interval scale ( i.e., the distance from "very bad" to "bad" is equal to the distance from "good to very good"). in that case you could calculate means and compare those means using a t-test.

Can a chi square be used for likert scale?

If you go through from the literature then you will find that both test ( t test and chi square ) can be used for likert scale data. So if you use t test then you can also justify it and if you use chi sqaure test, it can also be justify.

Is there a fixed answer to the Likert scale?

There isn't a fixed answer without further information about the scale and the objectives. For instance, is it a proper Likert scale, a Likert-type scale or a single rating scale item.

Can you use the t-test to compare responses on the Likert scale?

sometime people use  the t-test to compare responses on likert scale but it is not appropratie

Is the t statistic arbitrary?

Means and variances are arbitrary with ordinal data, and hence the t statistic is arbitrary. With Likert data, the t test is inappropriate and uninterpretable.

When is a paired t-test appropriate?

t-test should be appropriate if the normality of your sample can be ascertained, your independent variable is in categorical form, and your dependent variable is in either interval or ratio scale. Kindly note that if the same group is tested repeatedly, a paired t-test is best, whereas if the groups are independent of each other, an independent sample t-test is best. I am sure this helps. Goodluck.

Can a paired t-test be conducted between control groups?

An Independent sample t-test can be conducted between the control group and experiment group, and paired sample t-test can be conducted within the group.

Can you subtract the final value of each subject from baseline?

Of course, you can subtract the final value of each subjects from baseline and compare the mean of the differences using “independent sample t-test” or Mann-Whitney U Test according the distribution of your dependent variables.

How to justify one's method?

In short, justifying one’s method by saying that it’s done only works when somebody down the line of citations has actually succeeded in providing a sound justification relevant to one’s particular study.

Which correlation model is used to predict the significance of the influence?

I recommend the Logit model. But, If you can simplify the Likert's scale to ordinal (yes/no or agree/disagree), I recommend Somer's D Correlation. With this model [ (Ordinal (dependent) / ordinal (independent)], you can predict the significance of the influence, the strength and the direction of the influence. This model is like the t-test but in non-parametric statistics

How to find the minimum and maximum of a Likert scale?

To determine the minimum and the maximum length of the 5-point Likert type scale, the range is calculated by (5 − 1 = 4) then divided by five as it is the greatest value of the scale (4 ÷ 5 = 0.80). Afterwards, number one which is the least value in the scale was added in order to identify the maximum of this cell. The length of the cells is determined below:

What is NHST used for?

NHST is used in medical research, neuroscience, business research, cognitive psychology, nursing research, sociology, and to a lesser extent even the life sciences and physical sciences. It was developed by Fisher, whom I think would be horrified by many of the ways researchers use "Fisherian" statistical significance testing. The critical literature on it has persisted from Fisher to today, and has become (in the opinion of some statisticians) so problematic there is at least one semi-popular, pretty non-technical book on the subject (Ziliak, S. T., & McCloskey, D. N. (2008). The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives. University of Michigan Press.).

What is the problem with Likert scales?

The problem is that every question with a Likert-type response format requires the participant to interpret the question in relation to the points on the scale in such a way as to allow a conceptual mapping from the realm of semantic & linguistic polysemy to numerical precision. That’s why problems like middle response biases arise, or why there exists disagreement over whether or not one should use e.g., a 7-point scale labeled only by the extremes (i.e., “strongly agree” on one side and “strongly disagree” on the other with the actual choices being numbers 1-7) or e.g., a 5-point scale with no numbers shown and each option a linguistic one. There is no direct map from the belief, attitude, opinion, etc., that the participant has which corresponds exactly to one and only one of 5,6, 7, 13, or more options.

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Can categorical responses be independent measures?

There exist a few approaches to this issue. The easiest is to assert it doesn’t exist, and you can treat 5 ranked categorical responses as independent measures all normally distributed. The first paper I’ve attached is something akin to such a view.

What was the purpose of the study at Willowbrook?

The studies were designed to gain an understanding of the natural history of infectious hepatitis and subsequently to test the effects of gamma globulin in preventing or ameliorating the disease.

What does Joshua want to compare?

Joshua wants to compare past and present trends in the education of ESL children. This is an example of what type of research?

Which is the most likely explanation for differences between two groups?

Given no other information, chance is always the most likely explanation for differences between two groups.

Does Emily's school have an early intervention program?

Emily's school has implemented an early intervention program for at-risk students. In order to monitor its effectiveness on student performance, she would use which research method?

What Are Data Analysis Methods?

Quantitative Data Analysis Methods

Qualitative Data Analysis Methods

How to Choose A Data Analysis Method

• Which data analysis method you choose will depend greatly on the dataset you are dealing with and what you intend to achieve with it. If your dataset consists of quantitative data, you’ll have to use a quantitative method; if your dataset consists of qualitative data, you’ll have to use a qualitative method. In the case of quantitative data analysi...

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