APA Reporting SPSS Factor Analysis

• Introduction
• Creating APA Tables - the Easy Way
• Table I - Factor Loadings & Communalities
• Table II - Total Variance Explained
• Table III - Factor Correlations

Introduction

Creating APA style tables from SPSS factor analysis output can be cumbersome. This tutorial therefore points out some tips, tricks & pitfalls. We'll use the results of SPSS Factor Analysis - Intermediate Tutorial.

All analyses are based on 20-career-ambitions-pca.sav (partly shown below).

Note that some items were reversed and therefore had “(R)” appended to their variable labels;
We'll FILTER out cases with 10 or more missing values.

After opening these data, you can replicate the final analyses by running the SPSS syntax below.

Creating APA Tables - the Easy Way

For a wide variety of analyses, the easiest way to create APA style tables from SPSS output is usually to

1. adjust your analyses in SPSS so the output is as close as possible to the desired end results. Changing table layouts (which variables/statistics go into which rows/columns?) is also best done here.
2. copy-paste one or more tables into Excel or Googlesheets. This is the easiest way to set decimal places, fonts, alignment, borders and more;
3. copy-paste your table(s) from Excel into WORD. Perhaps adjust the table widths with “autofit”, and you'll often have a perfect end result.

Autofit to Contents, then Window results in optimal column widths

Table I - Factor Loadings & Communalities

The figure below shows an APA style table combining factor loadings and communalities for our example analysis.

Example APA style factor loadings table

If you take a good look at the SPSS output, you'll see that you cannot simply copy-paste these tables for combining them in Excel. This is because the factor loadings (pattern matrix) table follows a different variable order than the communalities table. Since the latter follows the variable order as specified in your syntax, the easiest fix for this is to

• make sure that only variable names (not labels) are shown in the output;
• copy-paste the correctly sorted pattern matrix into Excel;
• copy-paste the variable names into the FACTOR syntax and rerun it.

Tip: try and replace the line breaks between variable names by spaces as shown below.

Replace line breaks by spaces in an SPSS syntax window

Also, you probably want to see only variable labels (not names) from now on. And -finally- we no longer want to hide any small absolute factor loadings shown below.

This table is fine for an exploratory analysis but not for reporting

The syntax below does all that and thus creates output that is ideal for creating APA style tables.

You can now safely combine the communalities and pattern matrix tables and make some final adjustments. The end result is shown in this Googlesheet, partly shown below.

An APA table for WORD is best created in a Googlesheet or Excel

Since decimal places, fonts, alignment and borders have all been set, this table is now perfect for its final copy-paste into WORD.

Table II - Total Variance Explained

The screenshot below shows how to report the Eigenvalues table in APA style.

APA style Eigenvalues example table

The corresponding SPSS output table comes fairly close to this. However, an annoying problem are the missing percent signs.

If we copy-paste into Excel and set a percentage format, 34.57 is converted into 3,457%. This is because Excel interprets these numbers as proportions rather than percentage points as SPSS does. The easiest fix is setting a percent format for these columns in SPSS before copy-pasting into Excel.

The OUTPUT MODIFY example below does just that for all Eigenvalues tables in the output window.

After this tiny fix, you can copy-paste this table from SPSS into Excel. We can now easily make some final adjustments (including the removal of some rows and columns) and copy-paste this table into WORD.

Table III - Factor Correlations

If you used an oblique factor rotation, you'll probably want to report the correlations among your factors. The figure below shows an APA style factor correlations table.

The corresponding SPSS output table (shown below) is pretty different from what we need.

APA style factor correlation table

Adjusting this table manually is pretty doable. However, I personally prefer to use an SPSS Python script for doing so.

You can download my script from LAST-FACTOR-CORRELATION-TABLE-TO-APA.sps. This script is best run from an INSERT command as shown below.

I highly recommend trying this script but it does make some assumptions:

• the above syntax assumes the script is located in D:\DOWNLOADS so you probably need to change that;
• the script assumes that you've the SPSS Python3.x essentials properly installed (usually the case for recent SPSS versions);
• the script assumes that no SPLIT FILE is in effect.

If you've any trouble or requests regarding my script, feel free to contact me and I'll see what I can do.

Final Notes

Right, so these are the basic routines I follow for creating APA style factor analysis tables. I hope you'll find them helpful.

If you've any feedback, please throw me a comment below.

Thanks for reading!

Creating APA Style Contingency Tables in SPSS

Running simple contingency tables in SPSS is easy enough. However, the default format is inconvenient and doesn't meet APA standards. This tutorial walks you through 3 options for creating the desired tables:

• CROSSTABS is easy but requires some (manual) editing.
• CTABLES is faster but a bit harder and requires a custom tables license.
• TABLES is fast but rather challenging.

We'll use bank_clean.sav -partly shown below- for all examples. You can try them yourself after downloading the data.

So What Are Contingency Tables Anyway?

Contingency tables show frequencies for all
combinations of values of 2(+) variables. For example, the table below shows a contingency table -or “crosstab”- for 2 variables: marital status and education level.

Only 1 respondent had middle school and never married;
A total of 123 respondents never married;
Only 4 respondents have middle school or lower;
The table shows all combinations of marital status and education for 442 respondents.

Hopefully, contingency tables give some insight into the association -if any- between these variables. So how does that work? For a very simple explanation, see

• Chi-Square Independence Test - Quick Introduction or
• Cramér’s V - What and Why?

Running Simple Contingency Tables in SPSS

The fastest way to create the table we just saw is running one line of SPSS syntax: crosstabs educ by marit. The categories of the first variable -educ or education- become rows in the table. The values of the second variable -marit or marital status- become the columns. As a rule of thumb, the columns hold the groups you want to compare on whatever goes into the rows. In this case, we're comparing marital status groups on education level.
If we had wanted to do the reverse -compare education level groups on marital status- we'd swap the rows and columns and run crosstabs marit by educ.

CROSSTABS with Column Percentages

Right. So how do our groups compare on education level? It's hard to see from our first table because each marital status group has a different n or sample size. We may see more of a pattern if we add column percentages. The syntax below does just that.

Result

If we study the entire table, it seems that widowed respondents are somewhat higher educated than the others: no less than 56.8% hold a master's degree and another 13.5% even a PhD. The overall pattern is not very clear though and we'd perhaps better visualize it as a stacked bar chart.
In any case, the table format -percentages in rows- doesn't really help either and doesn't meet APA guidelines. So let's fix it.

Converting CROSSTABS to APA Tables

One solution is right-click our table and select Edit content In Separate Window In the pivot editor that opens, tick Pivoting trays as shown below.

Now drag and drop statistics right underneath Marital status and just close the window.

Let's now make 2 text replacements:

• use n instead of “Count”
• use % instead of “% within Marital status”

Using the Ctrl + H shortkey in the output viewer should work. Or -much nicer- use the OUTPUT MODIFY syntax below if you're on SPSS version 22 or higher.

Result

APA Contingency Table Created with CROSSTABS

So that's the easiest way to create an APA style contingency table in SPSS. But -personally- I find it too much work, especially for several tables. So let's consider 2 alternatives.

APA Contingency Tables from CTABLES

The table we just created can be run in one go with CTABLES. However, this only works if you've a license for the custom tables module. You can check this by running show license. If the resulting table includes “Custom Tables”, try the syntax below.

Result

APA Contingency Table Created with CTABLES

CTABLES works great for this table but -unfortunately- you'll need a separate command for each table. The syntax is also somewhat challenging. I think you could paste it from Analyze Tables Custom Tables but I somehow never get the results I want from the menu.
A better way perhaps is to copy-paste-edit the syntax example for several tables. Or create and run the commands with Python for SPSS. This is faster but also harder. But if you like it fast and hard -I surely do- then go for it.

APA Contingency Tables from TABLES

So what if you don't have a license for CTABLES? Well, then there's TABLES. TABLES was replaced by CTABLES around 1990 and removed from all documentation. But -as very very few SPSS users know- TABLES still works in all recent SPSS versions.
Like so, the syntax below is an alternative for the CTABLES approach.

Result

APA Contingency Table Created with TABLES

This contingency table is almost identical to the CTABLES result. Unfortunately, the syntax is even harder and -worse- not documented. We might build a tool for creating the TABLES command from the menu but it won't come up any time soon.

Final Notes

We showed 3 ways for creating APA style contingency tables in SPSS:

• CROSSTABS is easiest. You can create several tables in one go but they require quite some (manual) editing.
• CTABLES runs the desired table straight away and could be run from the menu. However, it creates one table at the time and requires an additional license.
• TABLES also comes up with the right table straight away. However, the syntax is difficult and there's no menu.

Admittedly, none of these options is ideal. So we might build a tool some time that runs many tables in one go from the menu.

Thanks for reading!

Creating APA Style Frequency Tables in SPSS

The most basic table in statistics is probably a simple frequency distribution. Sadly, basic frequency tables from SPSS are monstrous. On top of that, they don't meet APA recommendations.
So how to create better frequency tables -preferably fast? This tutorial shows a cool trick for doing just that! We'll use bank_clean.sav throughout, part of which is shown below.

Why Basic SPSS Frequency Tables Suck

So let's take a close look at some basic frequency tables. We'll create some by running the syntax below.

Result

For just inspecting your data, this may do. However, these tables are not suitable for reporting:

• SPSS users surely know the difference between valid and missing values. However, clients who don't use SPSS often find this confusing.
• “Total” appears no less than 3 times in our tables.
• Percent signs are missing from percentages.
• We rarely need cumulative frequencies -which are really cumulative valid frequencies.
• The new styling for output tables -introduced in SPSS 23- looks disastrous.

Now, the styling is easily fixed with a tablelook. After applying it, our table looks much better as shown below.

Unfortunately, FREQUENCIES has no options for avoiding the other issues we just mentioned. So let's try something completely different.

Frequencies in MEANS Tables

Ok, this'll sound crazy but -really- do give it a go. First off, we'll create a new variable holding zeroes for all cases. Next, we'll run a minimal MEANS table for our constant by our target variables. Let's run the syntax below and see what happens.

Result

Our table looks stupid. Obviously, all means and standard deviations are 0.000. However, we do have clean and simple frequencies but we don't have the corresponding percentages. Yet.

MEANS without Means

Now the trick is that MEANS allows us to choose which columns we want in which order. Therefore, we can have MEANS without means or standard deviations but with frequencies and percentages. This results in nice and clean frequency tables in the APA recommended format.

Result

First note that we set part of the desired table title as a variable label for our constant. If you don't want that, try and run variable labels constant ' '. After doing so, the title consists of a single space so there seems to be no title at all.
Also note that we prettified our tables with OUTPUT MODIFY which requires SPSS version 22 or higher. For keeping it simple, we processed all tables in the output window. If you don't want that, adding one or two lines to OUTPUT MODIFY restricts the modifications to a precise selection of tables.
If you're on SPSS 21 or lower, the Ctrl + H shortkey -either in the output window or after exporting to WORD- may help in removing or replacing text.

Including User Missing Values

By default, our approach includes only valid values. However, including user missing values is easily done by just adding a single line to the syntax.

Including System Missing Values

Very few SPSS procedures can include system missing values. However, that's easily solved: we'll use a simple RECODE to change them to some huge number. We then give that a value label and set it as missing.
Quick tip: don't use very small numbers such as -9999 for this. Small numbers often end up as the first -rather than the last- rows in your tables.

Result

APA Frequency Tables from CTABLES

For me, creating frequency tables like we just discussed is the preferred option. It's fast and simple. However, an alternative is using CTABLES but this requires a license for the custom tables option.
CTABLES can create a single frequency table for multiple variables in one go. The syntax below presents a minimal example for doing so.

Result

So that'll do for our frequency tables. I hope you found this tutorial helpful! Let me know by throwing in a comment below.

Thanks for reading!

Creating APA Style Descriptives Tables in SPSS

Running some basic descriptive statistics in SPSS is super easy with the DESCRIPTIVES command. However, the resulting table doesn't even come close to the APA required format or what corporate clients often demand.
So what's the problem? Well, you'll quickly find out if you try and create the table shown below.

Nice and clean APA descriptives table.

SPSS DESCRIPTIVES Example

This table is based on no_1 to no_5 in alcotest.sav. When trying to create it with DESCRIPTIVES, the closest I got was the syntax below.

Result

Although this table is very easy to create -and does a good job when exploring data- it's not quite what it should have been. So let's dive into some issues.

No Median in DESCRIPTIVES

For some weird reason, DESCRIPTIVES does not include the median. Seriously, I looked it up in the CSR and it's just not there.

Ok, then let's just skip the median for now and run into the second problem.

Undesired Inferential Statistics

For some statistics -including skewness and kurtosis- SPSS will automatically report their standard errors. But: if I want standard errors, I'll ask for them.

If I don't ask for them, then I probably don't want them. But I get them anyway. And I've several problems with that:

• The standard errors result in a complicated table format with merged cells. Removing or hiding these unwanted cells is complicated. At least, I haven't found a quick and easy way for doing so.
• Standard errors are not descriptive but -rather- inferential statistics. They are only correct if my data are a simple random sample from my population.
• If my data hold a substantive percentage of my population, these standard errors are biased (away from zero).In this case, I need to apply a so-called finity correction to the standard errors. The SPSS complex samples option (module) is needed to do so.
• If I sampled my entire population, the reported standard errors are nonsensical. In this case, there's no sampling error so the correct standard errors are all zero.

Undesired N Column

When I'm just exploring my data, I like to see the N per variable. It tells me how many missing values each variable has. But if I don't have any missings, I don't want this column. In this case, I rather report N in the title of my table. However, I can't omit N when using DESCRIPTIVES.

Can't Omit “Valid N (listwise)”

In a similar vein, DESCRIPTIVES always includes Valid N (listwise). This tells me how many cases have zero missing values on all variables included in my table. When preparing data -especially for a multivariate analysis- that's great. However, “Valid N (listwise)” puzzles my non SPSS using clients and they don't want to see it. Fortunately, an SPSS Python script does a fair job hiding it. Still, being able to choose whether to include it or not would be highly preferable over always including it and then having to hide it.
A similar point was made in SPSS Correlations in APA Format.

CELLS or STATISTICS?

• When running CROSSTABS, the CELLS subcommand specifies which cells my contingency table should hold.
  Next, a test for statistical significance -usually a chi-square independence test- can be specified with STATISTICS.STATISTICS in CROSSTABS also creates several correlations such as Pearson correlations, Cramér’s V, Spearman rank correlations and many other statistics.
• When running MEANS, the CELLS subcommand specifies which cells my means table should hold.
  Next, a test for statistical significance -a one-way ANOVA- can be specified with STATISTICS.
• When running DESCRIPTIVES, there's no CELLS subcommand.
  STATISTICS specifies which cells my descriptives table should hold.

Table Styling

If you're on SPSS version 22 or earlier, your descriptives table probably looks like the one shown below. Not super pretty but clean and decent.

For some reason, SPSS 23 introduced new table styles with grey text on -again- grey backgrounds. I don't like the way they look on screen, let alone when printed out.
If you like the old styles more than the new ones, you can revert to them by setting Original.stt as your tablelook. On my system, set tlook "C:\Program Files\IBM\SPSS\Statistics\24\Looks\Original.stt". does the trick.

Nicer Descriptives with MEANS

So how to create this descriptives table in APA format? Well, it's utterly simple. Just run means no_1 to no_5
/cells mean stddev median skew. and transpose the resulting table. Which leaves us with one question: how to transpose a table in SPSS?

Transposing Pivot Tables in SPSS

In contrast to chart templates, table templates can't transpose output for you -which is unfortunate because it would save a lot of time. So there's 3 options:

• Manually: right-click the table, select Edit Content In Separate Window and rearrange the pivoting trays. For an example, see SPSS Chi-Square Independence Test (scroll way down).
• Python: an SPSS Python script can transpose one, many or all pivot tables in your output window for you. This requires you have the SPSS Python Essentials properly installed.
• Last but not least, if you're on SPSS 22 or higher, OUTPUT MODIFY does the trick fast with little syntax. I'll add an example below.

Thanks for reading.

Creating APA Style Correlation Tables in SPSS

Introduction & Practice Data File

When running correlations in SPSS, we get the p-values as well. In some cases, we don't want that: if our data hold an entire population, such p-values are actually nonsensical. For some stupid reason, we can't get correlations without significance levels from the correlations dialog. However, this tutorial shows 2 ways for getting them anyway. We'll use adolescents-clean.sav throughout.

Correlation Table as Recommended by the APA

Option 1: FACTOR

A reasonable option is navigating to Analyze Dimension Reduction Factor as shown below.

Next, we'll move iq through wellb into the variables box and follow the steps outlines in the next screenshot.

Clicking Paste results in the syntax below. It'll create a correlation matrix without significance levels or sample sizes. Note that FACTOR uses listwise deletion of missing values by default but we can easily change this to pairwise deletion. Also, we can shorten the syntax quite a bit in case we need more than one correlation matrix.

Correlation Matrix from FACTOR Syntax

Result

When using pairwise deletion, we no longer see the sample sizes used for each correlation. We may not want those in our table but perhaps we'd like to say something about them in our table title.
More importantly, we've no idea which correlations are statistically significant and which aren't. Our second approach deals nicely with both issues.

Option 2: Adjust Default Correlation Table

The fastest way to create correlations is simply running correlations iq to wellb. However, we sometimes want to have statistically significant correlations flagged. We'll do so by adding just one line.

This results in a standard correlation matrix with all sample sizes and p-values. However, we'll now make everything except the actual correlations invisible.

Adjusting Our Pivot Table Structure

We first right-click our correlation table and navigate to Edit Content In Separate Window as shown below.

Select Pivoting Trays from the Pivot menu.

Drag and drop the Statistics (row) dimension into the LAYER area and close the pivot editor.

Result

Same Results Faster?

If you like the final result, you may wonder if there's a faster way to accomplish it. Well, there is: the Python syntax below makes the adjustment on all pivot tables in your output. So make sure there's only correlation tables in your output before running it. It may crash otherwise.

Well, that's it. Hope you liked this tutorial and my script -I actually run it from my toolbar pretty often.

Thanks for reading!