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SigmaPlot: Statistical Significance

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Hey guys,
I'm trying to add statistical significance data to a graph I have already generated on SigmaPlot (vertical bar with error bars). I have already generated the p values which determine the significance, but cannot find a way to add them to the graph.
I was thinking adding data labels above each bar on the graph (using asterisks to denote significance) would be a simple way to do it, but cannot figure out something that should be so simple.
Does anyone know how to add data labels to this type of chart?

Software info:
SigmaPlot for Windows Version 11.0
Build 11.1.0.102

Merge selected cells in Excel

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Hi all,

I am just in the process of formatting tables.

I am interested in merging a selection of cells. As you can in the picture file attached, they are highlighted in grey.

After selecting cells I want to merge, I right click and the merge option is immediately disabled.

Is there an easier way or do I have to individually merge every selection.
Attached Images
 

can't find R-square in Lisrel's output!!

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hello!

after a pass analysis, i can't find R-square in output!

where is it? should i check any item to see it ?


thanks in advance!

[LISREL 8.7] syntax for a formative second order model

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Hi:

I am developing a scale, which is theoretically a first order reflective, and second order formative model.
I have already analyzed the first order model and everything's ok, and results indicate that i should continue with a second order formative model.
I do not know how to write the syntax of the formative model, neither how to check that the results are acceptable.

I would really appreciate if anyone could help me with this.

Thanx in advance.

Two level label of x-axis?

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Hi all!

I would really appreciate your help on this...I am using Sigmaplot and I want to create a vertical bar chart with two levels of labeling at the x-axis.

Thank you very much in advance

TAXDIS using Primer 6.0

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I am trying to analyze AvTD and VarTD using Primer. My master list is saved as an Agg file. I have presence/absence species data for all my sites; how do I put it in he right format to analyze? Does it have to be a sample file? I am new at Primer and have tried all this using the manual but still cant figure it out. Any help will be much appreciated. Thanks.

[AMOS] - measurement model not great - is this the end of SEM for my data?

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Hello there,

This is my first attempt at SEM and I got as far as running my measurement model, with mixed results regarding goodness of fit. I've "tweaked" the model about as much as I can (removed a few items, covaried some error terms etc). Some of my fit stats are good, some awful. I've seen so much literature arguing that certain stats are inconclusive in SEM - not sure if this set is sufficient to proceed or whether I have to give up on SEM at this point - some opinions would be great (with references if you can). Many thanks.

PS: I have run with and without bootstrapping and got the same results (there is a multivariate kurtosis problem).

Using ML estimation with and without bootstrapping - same in each case
Chi-square p=.000 (one attempt at bootstrapping got as high as .006)
CMIN/DF 3.9
CFI .963
GFI .918
RMSEA .074
PCLOSE .000
TLI .952

Using ADF estimation (n=530 - not really enough for ADF)
Chi-square p=.000 (one attempt at bootstrapping got as high as .006)
CMIN/DF 2.798
CFI .782
GFI .876
RMSEA .058
PCLOSE .052
TLI .713

Please gurus - can I continue with SEM (and if so how do I justify that well enough for publication?). I don't even know if I can use regression with a multivariate kurtosis problem - next step is to investigate that.

Thanks.

[LISREL] Looking for a guide to understand output and modify measurement models

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Hi all,

I am hoping someone can help me as I am so close to the end of my dissertation I can taste it! Okay, so my methodologist suggested that I create a Path Analysis model to test the relationships of my data obtained by community college students who were enrolled in online courses. Here are the variables I have:

Predictors:
Advising Satisfaction (Ordinal, 3 points)
Online Adaptability Level (Ordinal, 3 points)

Outcome Variables:
Online Education Satisfaction (Ordinal, 3 points)
Enrollment Decision: (Nominal, 3 options: No Enroll, Enroll Online, Enroll on Campus)

Here are the relationships:
Online Education Satisfaction is predicted by Advising Satisfaction and Online Adaptability Level
Enrollment Decision is predicted by Advising Satisfaction and Online Education Satisfaction

So I can enter those into LISREL and get a pretty path diagram and then I can see the model fit indices (RMSEA, GFI, etc) in the output. But I am unsure how to determine whether or not any of the paths have any significance or how I can improve my model. Basically, I want to know how to determine when to add or remove paths (variances, covariances, etc) or other variables (I have about 14 entry variables I was trying to control Online Satisfaction for, but I don't want to enter those until I can understand how the values for the scaled scores above work). If anyone has a great reference to understand how to use LISREL in a measurement model setting and not latent, I'd greatly appreciate it. Thanks!

[AMOS] How to understand the Direct and Indirect Effect tables?

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Hi all,

I have finalized my model and am trying to understand the standardized direct and indirect effect tables i obtained using AMOS for my path analysis model. If I interpret correctly, the tables are printing all effects that are significant for each predictor. However, the results of my model match the standard regression weights which differs from the direct effects table. Can anyone provide some insight?

HLM_Problem with Missing Values

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I am using multilevel modeling to analyze data (HLM) for my dissertation. The problem I ran into is with importing the data into HLM. The data set has 26,000 observations. It's students nested within programs that is nested within institutions. I removed all the missing values in STATA before importing it into HLM. After removal of all the missing values, the data set was cut down to 20,000 observations. However, when I tried to create an HLM data set, there was only 2,500 observations imported at level one. I just can't figure out how to solve this issue.

Any idea where I might have done wrong?

AM software for NAAL dataset

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Hi,
Anybody familiar with AM software? and the NAAL dataset from 2003? I have downloaded both, but cant run any tests. It wont let me select any dep variables or export to excel.

thanks

A Question About Statistica

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Hi all. I want to ask a question about Probit Regression ın Statistica 7(Statsoft). There are 4 vairable types in Statistica 7 when you want to use probit regression. These are: Dependent, Categ.(Factors), Continious predictors,Count data. I know the meanings of dependent variable and continious predictors. But what does Categ.(Factors) and Count data mean? Categ.(Factors) mean Covariate or somethin like that? It would be great ıf you give some information about my questions. Thanks from now.

x12 arima and rolling forecasting

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Hi
I've collected some data and i need to store the 1 forecast for each observation added to the series. The well common rolling forecast.
Do you know of any way to achieve that?
It's tedious to run aggregate each observation to perform the same adjustment with x12.
Thanks for your time and patience.

[Lisrel] Cross-lagged panel model

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Hey,

I would like to use a cross-lagged panel model in Lisrel but somehow I'm not able to enter it in Lisrel. Can someone tip me off how to enter this model into Lisrel? All variables are observed.

Variables mindfulness observed at baseline, 3month, 15month
Variable depression observed at baseline, 3, 6, 9,12,15 month.
Between baseline and 3 month a mindfulness intervention took place I'm interested to what extend mindfulness at time 3 can predict levels of depression at 6, 9, 12, 15 month.


!IDST0 = measure of depression at baseline
!TotalT0 = measure of mindfulness at baseline

Syntax input:

Observed variables:
IDST0 IDST3 IDST6 IDST9 IDST12 IDST15 TotalT0 TotalT3 TotalT15
Correlation matrix:
….
Sample size = 248
Equations:
TotalT3 = TotalT0
TotalT15=Total15

IDST3 = IDST0
IDST6 = IDST3
IDST9 = IDST6
IDST12 = IDST9
IDST15 = IDST12

IDST6 = TotalT3
IDST9 = TotalT6

Options: EF
Path diagram


Okecomputer

[LISREL SIMPLIS] help with scalar invariance and calculating latent mean factors

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Hello,
I am conducting measurement equivalence on a two country sample (US and IN). I have established configural (baseline) and metric equivalence. However scalar invariance has not been established (the model change checks out but CFI change is less than .002). I examined the modification indices and for the most part I couldnt do much to improve fit. There were cross loadings or correlated errors and it didnt make theoretical sense to have cross loadings or correlate errors as the factors were different.So I didnt make any changes to the modification indices.
My question is how to i assess partial scalar invariance? Also once and if I etablish partial scalar invariance, I wanted to calculate group differences, however I would need to calculate the latent factors means, and Im not sure what the syntax is for that, or where in the output I could find this, if it is already provided in the scalar invariance output.
Does someone have any example syntax on getting partial scalar invariance or assessing latent factor means for group differences? I looked at Barbara Byrne's book for Lisrel but did not find it useful for these particular issues.

I look forward to any help! Thanks

AMOS: cannot save modified style sheet

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when I clicked on the blue arrowed indicated button, it popped out an error message.
what does this mean?

Thanks

Data Visualization - Further Step than Correspondence Analysis

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Hi,

I've currently been using correspondence to visualize our different consumer groups with each other.

I have been comparing my column groups (AA, BB, CC) with my row groups (A, B, C). The cross section of groups all have affinities with each other that I've been able to use XLSTAT to visualize the relationship (e.g. AA is closely tied to B).

However, I also have data showing the affinity between AA and BB, AA and CC, A and B, A and C, etc. Correspondence analysis will only show the visualization between the row and columns, but not with each other. I'd like to see at the same time how closely related AA is to BB, etc.

So I have a matrix with columns (AA, BB, CC, A, B, C) and rows (AA, BB, CC, A, B, C). What kind of data visualization analysis can graph all these affinities for me? Which software would be appropriate for my use?

Thanks,

Data overlap

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I'm looking at a number of datasets which are all representative of the UK (there is little to no skew in each database - all representative of the UK adult population). Adult population in the country is 48m. The databases in order of size are:
19m
12m
4m
4m
4m
3m
1m
0.5m
0.5m

I'm trying to calculate the net number of records I'm likely to achieve by matching these datasets together. Clearly it will be larger than 19m. What excel formula can I use to create a estimation on the net number of records?

Mplus code for testing mediation, moderation, and moderated mediation type hypotheses

Exploratory Structural Equation Modeling Mplus syntax

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Most of the Mplus syntax I have seen using ESEM is as follows:

f1-f3 by y301-y313 (*1);

You would get the same results using an EFA with a 3-factor solution.

This next example seems like a proper ESEM model:

f1-f2 BY y1-y6 (*1); f3 BY y7-y9;
f4 BY y10-y12;
f3 ON f1-f2;
f4 ON f3;

Which has both an EFA/CFA component, which is what I thought an ESEM model were.

I guess I'm confused by people's use of ESEM and most of the models look like an EFA to me in Mplus. Any clarification would be great beyond knowing ESEM provides SE.

Thank you for your help.
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